import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from scipy import stats
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import KFold
from sklearn.metrics import mean_squared_error
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error, mean_squared_log_error
df=pd.read_csv(r"C:\Users\prabha\Desktop\Dataset\energy-pop-exposure-nuclear-plants-locations\energy-pop-exposure-nuclear-plants-locations_plants.csv")
df
| FID | Region | Country | Plant | NumReactor | Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | ... | p10r_600 | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | Europe - Western | SWEDEN | AGESTA | 1 | 59.206022 | 18.082872 | 187382000 | 188684000 | 188250000 | ... | 8972550.0 | 5013240.0 | 5227700.0 | 5471110.0 | 3426880.0 | 3596030.0 | 3764920.0 | 1586350.0 | 1631670.0 | 1706190 |
| 1 | 1 | Europe - Western | SPAIN | ALMARAZ | 2 | 39.808100 | -5.696940 | 136675000 | 147718000 | 163429000 | ... | 19453700.0 | 17756500.0 | 18187800.0 | 20185200.0 | 10986000.0 | 11415400.0 | 12689800.0 | 6770480.0 | 6772380.0 | 7495340 |
| 2 | 2 | America - Latin | BRAZIL | ANGRA | 3 | -23.007857 | -44.458098 | 99195200 | 113894000 | 127898000 | ... | 18605600.0 | 39546400.0 | 44701700.0 | 50210600.0 | 32788500.0 | 37064600.0 | 41648300.0 | 6757940.0 | 7637110.0 | 8562300 |
| 3 | 3 | America - Northern | UNITED STATES OF AMERICA | ARKANSAS ONE | 2 | 35.310320 | -93.231289 | 117830000 | 132729000 | 146482000 | ... | 9498240.0 | 5603180.0 | 6226360.0 | 6866840.0 | 3779400.0 | 4198920.0 | 4633770.0 | 1823770.0 | 2027450.0 | 2233070 |
| 4 | 4 | Europe - Western | SPAIN | ASCO | 2 | 41.200000 | 0.566670 | 271854000 | 287134000 | 308922000 | ... | 17594700.0 | 14398500.0 | 15095600.0 | 16830700.0 | 11215400.0 | 11773600.0 | 13151300.0 | 3183180.0 | 3322050.0 | 3679470 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | 271 | Asia - Far East | CHINA | YANGJIANG | 3 | 21.708333 | 112.261111 | 557032000 | 629419000 | 679747000 | ... | 86375000.0 | 68115100.0 | 87136800.0 | 93428600.0 | 41415700.0 | 53433600.0 | 57372000.0 | 26699400.0 | 33703200.0 | 36056500 |
| 272 | 272 | America - Northern | UNITED STATES OF AMERICA | YANKEE | 1 | 42.727839 | -72.929108 | 123430000 | 131527000 | 145162000 | ... | 9951640.0 | 35873400.0 | 37247000.0 | 41124300.0 | 32253500.0 | 33508100.0 | 37010000.0 | 3619890.0 | 3738910.0 | 4114260 |
| 273 | 273 | Asia - Far East | KOREA, REPUBLIC OF | YONGGWANG | 6 | 35.411130 | 126.416190 | 649425000 | 710033000 | 750775000 | ... | 35715500.0 | 42866100.0 | 46496100.0 | 48569700.0 | 36191700.0 | 39809100.0 | 41589500.0 | 6674350.0 | 6686990.0 | 6980200 |
| 274 | 274 | Europe - Central and Eastern | UKRAINE | ZAPOROZHE | 6 | 47.511809 | 34.585460 | 273432000 | 274834000 | 272561000 | ... | 22931000.0 | 20624400.0 | 19361900.0 | 17990600.0 | 13838800.0 | 12978800.0 | 12067100.0 | 6785590.0 | 6383160.0 | 5923510 |
| 275 | 275 | America - Northern | UNITED STATES OF AMERICA | ZION | 2 | 42.446428 | -87.803003 | 162525000 | 176001000 | 194245000 | ... | 11318900.0 | 19702800.0 | 21460200.0 | 23696900.0 | 16653600.0 | 18285600.0 | 20199900.0 | 3049180.0 | 3174560.0 | 3497080 |
276 rows × 61 columns
missing_values = df.isnull()
missing_count = missing_values.sum()
missing_percentage = (missing_count / len(df)) * 100
print("Missing and Null Values:\n", missing_count)
print("Missing and Null Values (%):\n", missing_percentage)
Missing and Null Values:
FID 0
Region 3
Country 0
Plant 0
NumReactor 0
..
p00u_300 0
p10u_300 0
p90r_300 0
p00r_300 0
p10r_300 0
Length: 61, dtype: int64
Missing and Null Values (%):
FID 0.000000
Region 1.086957
Country 0.000000
Plant 0.000000
NumReactor 0.000000
...
p00u_300 0.000000
p10u_300 0.000000
p90r_300 0.000000
p00r_300 0.000000
p10r_300 0.000000
Length: 61, dtype: float64
df.dropna(axis='columns', inplace=True)
columns_to_drop = ['FID', 'Plant', 'NumReactor']
df.drop(columns=columns_to_drop, inplace=True)
df
| Country | Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | p90u_1200 | p00u_1200 | p10u_1200 | p90r_1200 | ... | p10r_600 | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | SWEDEN | 59.206022 | 18.082872 | 187382000 | 188684000 | 188250000 | 121178000.0 | 122299000.0 | 122399000.0 | 66203700 | ... | 8972550.0 | 5013240.0 | 5227700.0 | 5471110.0 | 3426880.0 | 3596030.0 | 3764920.0 | 1586350.0 | 1631670.0 | 1706190 |
| 1 | SPAIN | 39.808100 | -5.696940 | 136675000 | 147718000 | 163429000 | 87539700.0 | 93943200.0 | 103704000.0 | 49135800 | ... | 19453700.0 | 17756500.0 | 18187800.0 | 20185200.0 | 10986000.0 | 11415400.0 | 12689800.0 | 6770480.0 | 6772380.0 | 7495340 |
| 2 | BRAZIL | -23.007857 | -44.458098 | 99195200 | 113894000 | 127898000 | 67751500.0 | 77821400.0 | 87432200.0 | 31443800 | ... | 18605600.0 | 39546400.0 | 44701700.0 | 50210600.0 | 32788500.0 | 37064600.0 | 41648300.0 | 6757940.0 | 7637110.0 | 8562300 |
| 3 | UNITED STATES OF AMERICA | 35.310320 | -93.231289 | 117830000 | 132729000 | 146482000 | 92609500.0 | 104781000.0 | 115697000.0 | 25220200 | ... | 9498240.0 | 5603180.0 | 6226360.0 | 6866840.0 | 3779400.0 | 4198920.0 | 4633770.0 | 1823770.0 | 2027450.0 | 2233070 |
| 4 | SPAIN | 41.200000 | 0.566670 | 271854000 | 287134000 | 308922000 | 190825000.0 | 200465000.0 | 215092000.0 | 81029500 | ... | 17594700.0 | 14398500.0 | 15095600.0 | 16830700.0 | 11215400.0 | 11773600.0 | 13151300.0 | 3183180.0 | 3322050.0 | 3679470 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | CHINA | 21.708333 | 112.261111 | 557032000 | 629419000 | 679747000 | 250848000.0 | 287891000.0 | 309439000.0 | 306184000 | ... | 86375000.0 | 68115100.0 | 87136800.0 | 93428600.0 | 41415700.0 | 53433600.0 | 57372000.0 | 26699400.0 | 33703200.0 | 36056500 |
| 272 | UNITED STATES OF AMERICA | 42.727839 | -72.929108 | 123430000 | 131527000 | 145162000 | 103377000.0 | 110101000.0 | 121564000.0 | 20052600 | ... | 9951640.0 | 35873400.0 | 37247000.0 | 41124300.0 | 32253500.0 | 33508100.0 | 37010000.0 | 3619890.0 | 3738910.0 | 4114260 |
| 273 | KOREA, REPUBLIC OF | 35.411130 | 126.416190 | 649425000 | 710033000 | 750775000 | 404604000.0 | 440983000.0 | 464987000.0 | 244821000 | ... | 35715500.0 | 42866100.0 | 46496100.0 | 48569700.0 | 36191700.0 | 39809100.0 | 41589500.0 | 6674350.0 | 6686990.0 | 6980200 |
| 274 | UKRAINE | 47.511809 | 34.585460 | 273432000 | 274834000 | 272561000 | 162035000.0 | 163493000.0 | 162347000.0 | 111397000 | ... | 22931000.0 | 20624400.0 | 19361900.0 | 17990600.0 | 13838800.0 | 12978800.0 | 12067100.0 | 6785590.0 | 6383160.0 | 5923510 |
| 275 | UNITED STATES OF AMERICA | 42.446428 | -87.803003 | 162525000 | 176001000 | 194245000 | 131460000.0 | 142393000.0 | 157233000.0 | 31065000 | ... | 11318900.0 | 19702800.0 | 21460200.0 | 23696900.0 | 16653600.0 | 18285600.0 | 20199900.0 | 3049180.0 | 3174560.0 | 3497080 |
276 rows × 57 columns
from sklearn.preprocessing import LabelEncoder
# Label Encoding
label_encoder = LabelEncoder() # Create a LabelEncoder instance
categorical_cols = [ 'Country'] # Specify the categorical columns to be encoded
for col in categorical_cols:
df[col + '_encoded'] = label_encoder.fit_transform(df[col]) # Apply label encoding to each column
print("Label Encoded Data:")
df
Label Encoded Data:
| Country | Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | p90u_1200 | p00u_1200 | p10u_1200 | p90r_1200 | ... | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | Country_encoded | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | SWEDEN | 59.206022 | 18.082872 | 187382000 | 188684000 | 188250000 | 121178000.0 | 122299000.0 | 122399000.0 | 66203700 | ... | 5013240.0 | 5227700.0 | 5471110.0 | 3426880.0 | 3596030.0 | 3764920.0 | 1586350.0 | 1631670.0 | 1706190 | 28 |
| 1 | SPAIN | 39.808100 | -5.696940 | 136675000 | 147718000 | 163429000 | 87539700.0 | 93943200.0 | 103704000.0 | 49135800 | ... | 17756500.0 | 18187800.0 | 20185200.0 | 10986000.0 | 11415400.0 | 12689800.0 | 6770480.0 | 6772380.0 | 7495340 | 27 |
| 2 | BRAZIL | -23.007857 | -44.458098 | 99195200 | 113894000 | 127898000 | 67751500.0 | 77821400.0 | 87432200.0 | 31443800 | ... | 39546400.0 | 44701700.0 | 50210600.0 | 32788500.0 | 37064600.0 | 41648300.0 | 6757940.0 | 7637110.0 | 8562300 | 3 |
| 3 | UNITED STATES OF AMERICA | 35.310320 | -93.231289 | 117830000 | 132729000 | 146482000 | 92609500.0 | 104781000.0 | 115697000.0 | 25220200 | ... | 5603180.0 | 6226360.0 | 6866840.0 | 3779400.0 | 4198920.0 | 4633770.0 | 1823770.0 | 2027450.0 | 2233070 | 33 |
| 4 | SPAIN | 41.200000 | 0.566670 | 271854000 | 287134000 | 308922000 | 190825000.0 | 200465000.0 | 215092000.0 | 81029500 | ... | 14398500.0 | 15095600.0 | 16830700.0 | 11215400.0 | 11773600.0 | 13151300.0 | 3183180.0 | 3322050.0 | 3679470 | 27 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | CHINA | 21.708333 | 112.261111 | 557032000 | 629419000 | 679747000 | 250848000.0 | 287891000.0 | 309439000.0 | 306184000 | ... | 68115100.0 | 87136800.0 | 93428600.0 | 41415700.0 | 53433600.0 | 57372000.0 | 26699400.0 | 33703200.0 | 36056500 | 6 |
| 272 | UNITED STATES OF AMERICA | 42.727839 | -72.929108 | 123430000 | 131527000 | 145162000 | 103377000.0 | 110101000.0 | 121564000.0 | 20052600 | ... | 35873400.0 | 37247000.0 | 41124300.0 | 32253500.0 | 33508100.0 | 37010000.0 | 3619890.0 | 3738910.0 | 4114260 | 33 |
| 273 | KOREA, REPUBLIC OF | 35.411130 | 126.416190 | 649425000 | 710033000 | 750775000 | 404604000.0 | 440983000.0 | 464987000.0 | 244821000 | ... | 42866100.0 | 46496100.0 | 48569700.0 | 36191700.0 | 39809100.0 | 41589500.0 | 6674350.0 | 6686990.0 | 6980200 | 17 |
| 274 | UKRAINE | 47.511809 | 34.585460 | 273432000 | 274834000 | 272561000 | 162035000.0 | 163493000.0 | 162347000.0 | 111397000 | ... | 20624400.0 | 19361900.0 | 17990600.0 | 13838800.0 | 12978800.0 | 12067100.0 | 6785590.0 | 6383160.0 | 5923510 | 31 |
| 275 | UNITED STATES OF AMERICA | 42.446428 | -87.803003 | 162525000 | 176001000 | 194245000 | 131460000.0 | 142393000.0 | 157233000.0 | 31065000 | ... | 19702800.0 | 21460200.0 | 23696900.0 | 16653600.0 | 18285600.0 | 20199900.0 | 3049180.0 | 3174560.0 | 3497080 | 33 |
276 rows × 58 columns
df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 276 entries, 0 to 275 Data columns (total 58 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Country 276 non-null object 1 Latitude 276 non-null float64 2 Longitude 276 non-null float64 3 p90_1200 276 non-null int64 4 p00_1200 276 non-null int64 5 p10_1200 276 non-null int64 6 p90u_1200 276 non-null float64 7 p00u_1200 276 non-null float64 8 p10u_1200 276 non-null float64 9 p90r_1200 276 non-null int64 10 p00r_1200 276 non-null int64 11 p10r_1200 276 non-null int64 12 p90_30 276 non-null float64 13 p00_30 276 non-null float64 14 p10_30 276 non-null float64 15 p90u_30 276 non-null float64 16 p00u_30 276 non-null float64 17 p10u_30 276 non-null float64 18 p90r_30 276 non-null float64 19 p00r_30 276 non-null float64 20 p10r_30 276 non-null float64 21 p90_75 276 non-null float64 22 p00_75 276 non-null float64 23 p10_75 276 non-null float64 24 p90u_75 276 non-null float64 25 p00u_75 276 non-null float64 26 p10u_75 276 non-null float64 27 p90r_75 276 non-null float64 28 p00r_75 276 non-null float64 29 p10r_75 276 non-null float64 30 p90_150 276 non-null float64 31 p00_150 276 non-null float64 32 p10_150 276 non-null float64 33 p90u_150 276 non-null float64 34 p00u_150 276 non-null float64 35 p10u_150 276 non-null float64 36 p90r_150 276 non-null float64 37 p00r_150 276 non-null float64 38 p10r_150 276 non-null float64 39 p90_600 276 non-null float64 40 p00_600 276 non-null float64 41 p10_600 276 non-null float64 42 p90u_600 276 non-null float64 43 p00u_600 276 non-null float64 44 p10u_600 276 non-null float64 45 p90r_600 276 non-null float64 46 p00r_600 276 non-null float64 47 p10r_600 276 non-null float64 48 p90_300 276 non-null float64 49 p00_300 276 non-null float64 50 p10_300 276 non-null float64 51 p90u_300 276 non-null float64 52 p00u_300 276 non-null float64 53 p10u_300 276 non-null float64 54 p90r_300 276 non-null float64 55 p00r_300 276 non-null float64 56 p10r_300 276 non-null int64 57 Country_encoded 276 non-null int32 dtypes: float64(49), int32(1), int64(7), object(1) memory usage: 124.1+ KB
df.describe()
| Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | p90u_1200 | p00u_1200 | p10u_1200 | p90r_1200 | p00r_1200 | ... | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | Country_encoded | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| count | 276.000000 | 276.000000 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | ... | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 2.760000e+02 | 276.000000 |
| mean | 41.464873 | -0.833154 | 2.634335e+08 | 2.816791e+08 | 2.987191e+08 | 1.748656e+08 | 1.861499e+08 | 1.968991e+08 | 8.856783e+07 | 9.552691e+07 | ... | 3.052863e+07 | 3.270072e+07 | 3.456480e+07 | 2.238403e+07 | 2.387204e+07 | 2.517659e+07 | 8.144602e+06 | 8.828685e+06 | 9.388209e+06 | 21.347826 |
| std | 13.138551 | 75.441222 | 1.640597e+08 | 1.833881e+08 | 1.994596e+08 | 9.068376e+07 | 9.689716e+07 | 1.015562e+08 | 8.880513e+07 | 1.033398e+08 | ... | 2.180212e+07 | 2.422163e+07 | 2.590455e+07 | 1.593904e+07 | 1.695498e+07 | 1.764387e+07 | 8.890845e+06 | 1.066851e+07 | 1.208475e+07 | 11.002910 |
| min | -33.968002 | -124.209044 | 3.558760e+05 | 3.260370e+05 | 3.034580e+05 | 2.171250e+04 | 1.592310e+04 | 1.545940e+04 | 3.341640e+05 | 3.101140e+05 | ... | 3.586390e+04 | 3.641960e+04 | 3.453570e+04 | 7.970990e-01 | 7.348840e-01 | 6.874290e-01 | 3.586310e+04 | 3.641890e+04 | 3.453500e+04 | 0.000000 |
| 25% | 35.735645 | -77.396385 | 1.463155e+08 | 1.530615e+08 | 1.626702e+08 | 1.122075e+08 | 1.157828e+08 | 1.212025e+08 | 2.801438e+07 | 3.016952e+07 | ... | 1.344860e+07 | 1.439000e+07 | 1.516002e+07 | 8.849315e+06 | 1.001171e+07 | 1.033928e+07 | 2.499460e+06 | 2.590068e+06 | 2.853270e+06 | 10.000000 |
| 50% | 42.839200 | 4.720832 | 2.033275e+08 | 2.145620e+08 | 2.195720e+08 | 1.474715e+08 | 1.564245e+08 | 1.678680e+08 | 6.151855e+07 | 6.502695e+07 | ... | 2.455375e+07 | 2.584920e+07 | 2.758905e+07 | 1.755090e+07 | 1.924650e+07 | 2.069725e+07 | 5.178405e+06 | 5.339695e+06 | 5.597290e+06 | 23.000000 |
| 75% | 49.579176 | 30.497974 | 3.788732e+08 | 3.913535e+08 | 4.031740e+08 | 2.547372e+08 | 2.631975e+08 | 2.724995e+08 | 1.192925e+08 | 1.215025e+08 | ... | 4.479865e+07 | 4.662135e+07 | 4.966498e+07 | 3.533808e+07 | 3.770638e+07 | 3.972580e+07 | 1.017880e+07 | 1.043062e+07 | 1.063500e+07 | 33.000000 |
| max | 68.050658 | 166.539698 | 8.268430e+08 | 1.007240e+09 | 1.188970e+09 | 4.857500e+08 | 5.464730e+08 | 5.824590e+08 | 6.008490e+08 | 7.324380e+08 | ... | 1.154820e+08 | 1.531130e+08 | 1.784110e+08 | 6.816160e+07 | 7.082890e+07 | 7.296970e+07 | 7.945180e+07 | 1.031770e+08 | 1.202680e+08 | 33.000000 |
8 rows × 57 columns
z_scores = np.abs((df - np.mean(df,axis=0)) / np.std(df))
threshold = 3 # Adjust the threshold as needed
outliers_count = np.sum(z_scores > threshold)
print("Number of outliers:", outliers_count)
Number of outliers: Country 0 Country_encoded 0 Latitude 4 Longitude 0 p00_1200 4 p00_150 5 p00_30 8 p00_300 3 p00_600 4 p00_75 5 p00r_1200 4 p00r_150 3 p00r_30 4 p00r_300 5 p00r_600 6 p00r_75 4 p00u_1200 4 p00u_150 6 p00u_30 5 p00u_300 0 p00u_600 2 p00u_75 5 p10_1200 5 p10_150 5 p10_30 8 p10_300 3 p10_600 4 p10_75 6 p10r_1200 4 p10r_150 4 p10r_30 4 p10r_300 5 p10r_600 7 p10r_75 4 p10u_1200 4 p10u_150 7 p10u_30 5 p10u_300 0 p10u_600 2 p10u_75 5 p90_1200 4 p90_150 5 p90_30 6 p90_300 2 p90_600 3 p90_75 4 p90r_1200 4 p90r_150 3 p90r_30 5 p90r_300 5 p90r_600 5 p90r_75 3 p90u_1200 2 p90u_150 3 p90u_30 5 p90u_300 0 p90u_600 2 p90u_75 4 dtype: int64
C:\Users\prabha\Documents\Anaconda\lib\site-packages\numpy\core\fromnumeric.py:3430: FutureWarning: The default value of numeric_only in DataFrame.mean is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning. return mean(axis=axis, dtype=dtype, out=out, **kwargs) C:\Users\prabha\Documents\Anaconda\lib\site-packages\numpy\core\fromnumeric.py:3571: FutureWarning: The default value of numeric_only in DataFrame.std is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=None' is deprecated. Select only valid columns or specify the value of numeric_only to silence this warning. return std(axis=axis, dtype=dtype, out=out, ddof=ddof, **kwargs)
num_cols = [
'p90_1200', 'p00_1200', 'p10_1200', 'p90u_1200', 'p00u_1200', 'p10u_1200', 'p90r_1200', 'p00r_1200', 'p10r_1200',
'p90_30', 'p00_30', 'p10_30', 'p90u_30', 'p00u_30', 'p10u_30', 'p90r_30', 'p00r_30', 'p10r_30',
'p90_75', 'p00_75', 'p10_75', 'p90u_75', 'p00u_75', 'p10u_75', 'p90r_75', 'p00r_75', 'p10r_75',
'p90_150', 'p00_150', 'p10_150', 'p90u_150', 'p00u_150', 'p10u_150', 'p90r_150', 'p00r_150', 'p10r_150',
'p90_600', 'p00_600', 'p10_600', 'p90u_600', 'p00u_600', 'p10u_600', 'p90r_600', 'p00r_600', 'p10r_600',
'p90_300', 'p00_300', 'p10_300', 'p90u_300', 'p00u_300', 'p10u_300', 'p90r_300', 'p00r_300', 'p10r_300'
]
for col in num_cols:
# Calculate z-scores
z_scores = stats.zscore(df[col])
# Set the threshold for z-score outliers
threshold = 3
# Detect outliers
outliers = df[abs(z_scores) > threshold]
# Visualize outliers using box plots
plt.figure(figsize=(8, 6))
sns.boxplot(x=df[col])
plt.title(f"Boxplot of {col}")
plt.show()
# Print outlier details
print(f"Outliers in {col}:")
print(outliers)
Outliers in p90_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
167 103177000.0 120268000 12
201 37271400.0 39811200 6
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[4 rows x 58 columns]
Outliers in p00_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
167 103177000.0 120268000 12
201 37271400.0 39811200 6
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[4 rows x 58 columns]
Outliers in p10_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
123 48695900.0 56664800 12
167 103177000.0 120268000 12
201 37271400.0 39811200 6
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[5 rows x 58 columns]
Outliers in p90u_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
201 37271400.0 39811200 6
243 47354800.0 50583400 6
[2 rows x 58 columns]
Outliers in p00u_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
214 CHINA 29.101111 121.641944 722862000 811896000 865502000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
214 441405000.0 496909000.0 529558000.0 281457000 ... 60464400.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
214 68482800.0 73153500.0 40739400.0 46073000.0 49217400.0 19725000.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
201 37271400.0 39811200 6
214 22409800.0 23936100 6
243 47354800.0 50583400 6
[4 rows x 58 columns]
Outliers in p10u_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
214 CHINA 29.101111 121.641944 722862000 811896000 865502000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
214 441405000.0 496909000.0 529558000.0 281457000 ... 60464400.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
214 68482800.0 73153500.0 40739400.0 46073000.0 49217400.0 19725000.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
201 37271400.0 39811200 6
214 22409800.0 23936100 6
243 47354800.0 50583400 6
[4 rows x 58 columns]
Outliers in p90r_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
239 INDIA 19.828785 72.661201 568977000 700672000 820686000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
239 184165000.0 230100000.0 269807000.0 384812000 ... 53975200.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
239 69925300.0 81418700.0 28747300.0 37171700.0 43307300.0 25227900.0
p00r_300 p10r_300 Country_encoded
123 48695900.0 56664800 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
239 32753500.0 38111400 12
[4 rows x 58 columns]
Outliers in p00r_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
239 INDIA 19.828785 72.661201 568977000 700672000 820686000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
239 184165000.0 230100000.0 269807000.0 384812000 ... 53975200.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
239 69925300.0 81418700.0 28747300.0 37171700.0 43307300.0 25227900.0
p00r_300 p10r_300 Country_encoded
123 48695900.0 56664800 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
239 32753500.0 38111400 12
[4 rows x 58 columns]
Outliers in p10r_1200:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
239 INDIA 19.828785 72.661201 568977000 700672000 820686000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
239 184165000.0 230100000.0 269807000.0 384812000 ... 53975200.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
239 69925300.0 81418700.0 28747300.0 37171700.0 43307300.0 25227900.0
p00r_300 p10r_300 Country_encoded
123 48695900.0 56664800 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
239 32753500.0 38111400 12
[4 rows x 58 columns]
Outliers in p90_30:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
45 TAIWAN, CHINA 25.286254 121.587677 517341000 593088000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
132 KOREA, REPUBLIC OF 35.321269 129.294517 503755000 544728000
137 TAIWAN, CHINA 25.202723 121.662638 511038000 586271000
260 RUSSIAN FEDERATION 59.931389 30.258056 141911000 137868000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
45 637718000 302987000.0 348317000.0 374429000.0 214354000 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
132 572227000 335409000.0 362093000.0 379209000.0 168346000 ...
137 630625000 300245000.0 345428000.0 371500000.0 210794000 ...
260 133762000 92412000.0 89938100.0 87392900.0 49498600 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0
45 29644200.0 34080400.0 36758700.0 23587100.0 27024000.0 29176500.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
132 36899100.0 36583300.0 37780800.0 28302400.0 28161400.0 29099900.0
137 28023200.0 32218000.0 34776300.0 22612000.0 25923200.0 28007300.0
260 9019310.0 8281210.0 8047670.0 7446810.0 6826140.0 6633940.0
p90r_300 p00r_300 p10r_300 Country_encoded
39 33588400.0 37924300.0 40505100 6
45 6057090.0 7056470.0 7582200 30
125 8113520.0 10397900.0 12891800 21
132 8596700.0 8421880.0 8680890 17
137 5411170.0 6294880.0 6769010 30
260 1572500.0 1455070.0 1413740 23
[6 rows x 58 columns]
Outliers in p00_30:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
45 TAIWAN, CHINA 25.286254 121.587677 517341000 593088000
97 CHINA 22.597144 114.543139 615931000 702252000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
132 KOREA, REPUBLIC OF 35.321269 129.294517 503755000 544728000
137 TAIWAN, CHINA 25.202723 121.662638 511038000 586271000
147 CHINA 22.606110 114.553247 616314000 702669000
260 RUSSIAN FEDERATION 59.931389 30.258056 141911000 137868000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
45 637718000 302987000.0 348317000.0 374429000.0 214354000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
132 572227000 335409000.0 362093000.0 379209000.0 168346000 ...
137 630625000 300245000.0 345428000.0 371500000.0 210794000 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
260 133762000 92412000.0 89938100.0 87392900.0 49498600 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0
45 29644200.0 34080400.0 36758700.0 23587100.0 27024000.0 29176500.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
132 36899100.0 36583300.0 37780800.0 28302400.0 28161400.0 29099900.0
137 28023200.0 32218000.0 34776300.0 22612000.0 25923200.0 28007300.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0
260 9019310.0 8281210.0 8047670.0 7446810.0 6826140.0 6633940.0
p90r_300 p00r_300 p10r_300 Country_encoded
39 33588400.0 37924300.0 40505100 6
45 6057090.0 7056470.0 7582200 30
97 19904500.0 26459600.0 28317000 6
125 8113520.0 10397900.0 12891800 21
132 8596700.0 8421880.0 8680890 17
137 5411170.0 6294880.0 6769010 30
147 19925000.0 26481800.0 28340700 6
260 1572500.0 1455070.0 1413740 23
[8 rows x 58 columns]
Outliers in p10_30:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
45 TAIWAN, CHINA 25.286254 121.587677 517341000 593088000
97 CHINA 22.597144 114.543139 615931000 702252000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
132 KOREA, REPUBLIC OF 35.321269 129.294517 503755000 544728000
137 TAIWAN, CHINA 25.202723 121.662638 511038000 586271000
147 CHINA 22.606110 114.553247 616314000 702669000
260 RUSSIAN FEDERATION 59.931389 30.258056 141911000 137868000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
45 637718000 302987000.0 348317000.0 374429000.0 214354000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
132 572227000 335409000.0 362093000.0 379209000.0 168346000 ...
137 630625000 300245000.0 345428000.0 371500000.0 210794000 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
260 133762000 92412000.0 89938100.0 87392900.0 49498600 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0
45 29644200.0 34080400.0 36758700.0 23587100.0 27024000.0 29176500.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
132 36899100.0 36583300.0 37780800.0 28302400.0 28161400.0 29099900.0
137 28023200.0 32218000.0 34776300.0 22612000.0 25923200.0 28007300.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0
260 9019310.0 8281210.0 8047670.0 7446810.0 6826140.0 6633940.0
p90r_300 p00r_300 p10r_300 Country_encoded
39 33588400.0 37924300.0 40505100 6
45 6057090.0 7056470.0 7582200 30
97 19904500.0 26459600.0 28317000 6
125 8113520.0 10397900.0 12891800 21
132 8596700.0 8421880.0 8680890 17
137 5411170.0 6294880.0 6769010 30
147 19925000.0 26481800.0 28340700 6
260 1572500.0 1455070.0 1413740 23
[8 rows x 58 columns]
Outliers in p90u_30:
Country Latitude Longitude p90_1200 p00_1200 \
45 TAIWAN, CHINA 25.286254 121.587677 517341000 593088000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
132 KOREA, REPUBLIC OF 35.321269 129.294517 503755000 544728000
137 TAIWAN, CHINA 25.202723 121.662638 511038000 586271000
260 RUSSIAN FEDERATION 59.931389 30.258056 141911000 137868000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
45 637718000 302987000.0 348317000.0 374429000.0 214354000 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
132 572227000 335409000.0 362093000.0 379209000.0 168346000 ...
137 630625000 300245000.0 345428000.0 371500000.0 210794000 ...
260 133762000 92412000.0 89938100.0 87392900.0 49498600 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
45 29644200.0 34080400.0 36758700.0 23587100.0 27024000.0 29176500.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
132 36899100.0 36583300.0 37780800.0 28302400.0 28161400.0 29099900.0
137 28023200.0 32218000.0 34776300.0 22612000.0 25923200.0 28007300.0
260 9019310.0 8281210.0 8047670.0 7446810.0 6826140.0 6633940.0
p90r_300 p00r_300 p10r_300 Country_encoded
45 6057090.0 7056470.0 7582200 30
125 8113520.0 10397900.0 12891800 21
132 8596700.0 8421880.0 8680890 17
137 5411170.0 6294880.0 6769010 30
260 1572500.0 1455070.0 1413740 23
[5 rows x 58 columns]
Outliers in p00u_30:
Country Latitude Longitude p90_1200 p00_1200 \
45 TAIWAN, CHINA 25.286254 121.587677 517341000 593088000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
132 KOREA, REPUBLIC OF 35.321269 129.294517 503755000 544728000
137 TAIWAN, CHINA 25.202723 121.662638 511038000 586271000
260 RUSSIAN FEDERATION 59.931389 30.258056 141911000 137868000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
45 637718000 302987000.0 348317000.0 374429000.0 214354000 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
132 572227000 335409000.0 362093000.0 379209000.0 168346000 ...
137 630625000 300245000.0 345428000.0 371500000.0 210794000 ...
260 133762000 92412000.0 89938100.0 87392900.0 49498600 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
45 29644200.0 34080400.0 36758700.0 23587100.0 27024000.0 29176500.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
132 36899100.0 36583300.0 37780800.0 28302400.0 28161400.0 29099900.0
137 28023200.0 32218000.0 34776300.0 22612000.0 25923200.0 28007300.0
260 9019310.0 8281210.0 8047670.0 7446810.0 6826140.0 6633940.0
p90r_300 p00r_300 p10r_300 Country_encoded
45 6057090.0 7056470.0 7582200 30
125 8113520.0 10397900.0 12891800 21
132 8596700.0 8421880.0 8680890 17
137 5411170.0 6294880.0 6769010 30
260 1572500.0 1455070.0 1413740 23
[5 rows x 58 columns]
Outliers in p10u_30:
Country Latitude Longitude p90_1200 p00_1200 \
45 TAIWAN, CHINA 25.286254 121.587677 517341000 593088000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
132 KOREA, REPUBLIC OF 35.321269 129.294517 503755000 544728000
137 TAIWAN, CHINA 25.202723 121.662638 511038000 586271000
260 RUSSIAN FEDERATION 59.931389 30.258056 141911000 137868000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
45 637718000 302987000.0 348317000.0 374429000.0 214354000 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
132 572227000 335409000.0 362093000.0 379209000.0 168346000 ...
137 630625000 300245000.0 345428000.0 371500000.0 210794000 ...
260 133762000 92412000.0 89938100.0 87392900.0 49498600 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
45 29644200.0 34080400.0 36758700.0 23587100.0 27024000.0 29176500.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
132 36899100.0 36583300.0 37780800.0 28302400.0 28161400.0 29099900.0
137 28023200.0 32218000.0 34776300.0 22612000.0 25923200.0 28007300.0
260 9019310.0 8281210.0 8047670.0 7446810.0 6826140.0 6633940.0
p90r_300 p00r_300 p10r_300 Country_encoded
45 6057090.0 7056470.0 7582200 30
125 8113520.0 10397900.0 12891800 21
132 8596700.0 8421880.0 8680890 17
137 5411170.0 6294880.0 6769010 30
260 1572500.0 1455070.0 1413740 23
[5 rows x 58 columns]
Outliers in p90r_30:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
97 26459600.0 28317000 6
147 26481800.0 28340700 6
167 103177000.0 120268000 12
201 37271400.0 39811200 6
[5 rows x 58 columns]
Outliers in p00r_30:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
97 26459600.0 28317000 6
147 26481800.0 28340700 6
167 103177000.0 120268000 12
[4 rows x 58 columns]
Outliers in p10r_30:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
97 26459600.0 28317000 6
147 26481800.0 28340700 6
167 103177000.0 120268000 12
[4 rows x 58 columns]
Outliers in p90_75:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
97 CHINA 22.597144 114.543139 615931000 702252000
118 UNITED STATES OF AMERICA 41.271400 -73.952500 138491000 148816000
147 CHINA 22.606110 114.553247 616314000 702669000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
118 164264000 116270000.0 124903000.0 137925000.0 22220800 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0
118 43882200.0 45617300.0 50369700.0 39721900.0 41334900.0 45655000.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0
p90r_300 p00r_300 p10r_300 Country_encoded
39 33588400.0 37924300.0 40505100 6
97 19904500.0 26459600.0 28317000 6
118 4160310.0 4282350.0 4714700 33
147 19925000.0 26481800.0 28340700 6
[4 rows x 58 columns]
Outliers in p00_75:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
97 CHINA 22.597144 114.543139 615931000 702252000
118 UNITED STATES OF AMERICA 41.271400 -73.952500 138491000 148816000
147 CHINA 22.606110 114.553247 616314000 702669000
167 INDIA 28.159867 78.408658 818999000 1007240000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
118 164264000 116270000.0 124903000.0 137925000.0 22220800 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
167 1188970000 218150000.0 274801000.0 324681000.0 600849000 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0
118 43882200.0 45617300.0 50369700.0 39721900.0 41334900.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0
167 115482000.0 153113000.0 178411000.0 36030100.0 49936000.0
p10u_300 p90r_300 p00r_300 p10r_300 Country_encoded
39 57023100.0 33588400.0 37924300.0 40505100 6
97 62971100.0 19904500.0 26459600.0 28317000 6
118 45655000.0 4160310.0 4282350.0 4714700 33
147 62994700.0 19925000.0 26481800.0 28340700 6
167 58143700.0 79451800.0 103177000.0 120268000 12
[5 rows x 58 columns]
Outliers in p10_75:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
97 CHINA 22.597144 114.543139 615931000 702252000
118 UNITED STATES OF AMERICA 41.271400 -73.952500 138491000 148816000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
147 CHINA 22.606110 114.553247 616314000 702669000
167 INDIA 28.159867 78.408658 818999000 1007240000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
118 164264000 116270000.0 124903000.0 137925000.0 22220800 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
167 1188970000 218150000.0 274801000.0 324681000.0 600849000 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0
118 43882200.0 45617300.0 50369700.0 39721900.0 41334900.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0
167 115482000.0 153113000.0 178411000.0 36030100.0 49936000.0
p10u_300 p90r_300 p00r_300 p10r_300 Country_encoded
39 57023100.0 33588400.0 37924300.0 40505100 6
97 62971100.0 19904500.0 26459600.0 28317000 6
118 45655000.0 4160310.0 4282350.0 4714700 33
125 18487500.0 8113520.0 10397900.0 12891800 21
147 62994700.0 19925000.0 26481800.0 28340700 6
167 58143700.0 79451800.0 103177000.0 120268000 12
[6 rows x 58 columns]
Outliers in p90u_75:
Country Latitude Longitude p90_1200 p00_1200 \
6 GERMANY 50.903056 6.421111 377877000 387602000
97 CHINA 22.597144 114.543139 615931000 702252000
118 UNITED STATES OF AMERICA 41.271400 -73.952500 138491000 148816000
147 CHINA 22.606110 114.553247 616314000 702669000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
6 400550000 265023000.0 272376000.0 282369000.0 112854000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
118 164264000 116270000.0 124903000.0 137925000.0 22220800 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
6 71747700.0 75061700.0 76803300.0 55377400.0 57904900.0 59294500.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0
118 43882200.0 45617300.0 50369700.0 39721900.0 41334900.0 45655000.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0
p90r_300 p00r_300 p10r_300 Country_encoded
6 16370200.0 17156800.0 17508800 10
97 19904500.0 26459600.0 28317000 6
118 4160310.0 4282350.0 4714700 33
147 19925000.0 26481800.0 28340700 6
[4 rows x 58 columns]
Outliers in p00u_75:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
97 CHINA 22.597144 114.543139 615931000 702252000
118 UNITED STATES OF AMERICA 41.271400 -73.952500 138491000 148816000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
147 CHINA 22.606110 114.553247 616314000 702669000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
118 164264000 116270000.0 124903000.0 137925000.0 22220800 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0
118 43882200.0 45617300.0 50369700.0 39721900.0 41334900.0 45655000.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0
p90r_300 p00r_300 p10r_300 Country_encoded
39 33588400.0 37924300.0 40505100 6
97 19904500.0 26459600.0 28317000 6
118 4160310.0 4282350.0 4714700 33
125 8113520.0 10397900.0 12891800 21
147 19925000.0 26481800.0 28340700 6
[5 rows x 58 columns]
Outliers in p10u_75:
Country Latitude Longitude p90_1200 p00_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000
97 CHINA 22.597144 114.543139 615931000 702252000
118 UNITED STATES OF AMERICA 41.271400 -73.952500 138491000 148816000
125 PAKISTAN 24.845343 66.788517 362335000 468951000
147 CHINA 22.606110 114.553247 616314000 702669000
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... \
39 829594000 393377000.0 436918000.0 465857000.0 307954000 ...
97 758819000 314938000.0 362457000.0 390888000.0 300993000 ...
118 164264000 116270000.0 124903000.0 137925000.0 22220800 ...
125 562120000 130255000.0 170868000.0 204231000.0 232080000 ...
147 759257000 315206000.0 362753000.0 391203000.0 301107000 ...
p90_300 p00_300 p10_300 p90u_300 p00u_300 p10u_300 \
39 81160100.0 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0
97 64757000.0 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0
118 43882200.0 45617300.0 50369700.0 39721900.0 41334900.0 45655000.0
125 19337200.0 25170100.0 31379300.0 11223700.0 14772100.0 18487500.0
147 64798900.0 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0
p90r_300 p00r_300 p10r_300 Country_encoded
39 33588400.0 37924300.0 40505100 6
97 19904500.0 26459600.0 28317000 6
118 4160310.0 4282350.0 4714700 33
125 8113520.0 10397900.0 12891800 21
147 19925000.0 26481800.0 28340700 6
[5 rows x 58 columns]
Outliers in p90r_75:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
167 103177000.0 120268000 12
201 37271400.0 39811200 6
[3 rows x 58 columns]
Outliers in p00r_75:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
123 48695900.0 56664800 12
167 103177000.0 120268000 12
201 37271400.0 39811200 6
[4 rows x 58 columns]
Outliers in p10r_75:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
123 48695900.0 56664800 12
167 103177000.0 120268000 12
201 37271400.0 39811200 6
[4 rows x 58 columns]
Outliers in p90_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
121 JAPAN 36.458461 140.606342 150088000 153878000 155325000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
121 116253000.0 119213000.0 120223000.0 33834900 ... 52772100.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
121 55009400.0 55137900.0 43514200.0 45459400.0 45567000.0 9257910.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
p00r_300 p10r_300 Country_encoded
97 26459600.0 28317000 6
121 9550020.0 9570870 15
147 26481800.0 28340700 6
167 103177000.0 120268000 12
201 37271400.0 39811200 6
[5 rows x 58 columns]
Outliers in p00_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
237 CHINA 21.917778 112.981944 575483000 653428000 707083000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
237 272990000.0 314491000.0 339614000.0 302493000 ... 61722200.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
237 80251900.0 86074100.0 39459400.0 51303500.0 55097200.0 22262800.0
p00r_300 p10r_300 Country_encoded
97 26459600.0 28317000 6
147 26481800.0 28340700 6
167 103177000.0 120268000 12
201 37271400.0 39811200 6
237 28948400.0 30977000 6
[5 rows x 58 columns]
Outliers in p10_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
237 CHINA 21.917778 112.981944 575483000 653428000 707083000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
237 272990000.0 314491000.0 339614000.0 302493000 ... 61722200.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
237 80251900.0 86074100.0 39459400.0 51303500.0 55097200.0 22262800.0
p00r_300 p10r_300 Country_encoded
97 26459600.0 28317000 6
147 26481800.0 28340700 6
167 103177000.0 120268000 12
201 37271400.0 39811200 6
237 28948400.0 30977000 6
[5 rows x 58 columns]
Outliers in p90u_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
121 JAPAN 36.458461 140.606342 150088000 153878000 155325000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
245 JAPAN 36.466624 140.609604 150073000 153861000 155307000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
121 116253000.0 119213000.0 120223000.0 33834900 ... 52772100.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
245 116229000.0 119186000.0 120195000.0 33843900 ... 52762100.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
121 55009400.0 55137900.0 43514200.0 45459400.0 45567000.0 9257910.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
245 54998500.0 55127000.0 43501900.0 45446600.0 45554200.0 9260260.0
p00r_300 p10r_300 Country_encoded
121 9550020.0 9570870 15
201 37271400.0 39811200 6
245 9551980.0 9572840 15
[3 rows x 58 columns]
Outliers in p00u_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
121 JAPAN 36.458461 140.606342 150088000 153878000 155325000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
237 CHINA 21.917778 112.981944 575483000 653428000 707083000
245 JAPAN 36.466624 140.609604 150073000 153861000 155307000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
121 116253000.0 119213000.0 120223000.0 33834900 ... 52772100.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
237 272990000.0 314491000.0 339614000.0 302493000 ... 61722200.0
245 116229000.0 119186000.0 120195000.0 33843900 ... 52762100.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
121 55009400.0 55137900.0 43514200.0 45459400.0 45567000.0 9257910.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
237 80251900.0 86074100.0 39459400.0 51303500.0 55097200.0 22262800.0
245 54998500.0 55127000.0 43501900.0 45446600.0 45554200.0 9260260.0
p00r_300 p10r_300 Country_encoded
97 26459600.0 28317000 6
121 9550020.0 9570870 15
147 26481800.0 28340700 6
201 37271400.0 39811200 6
237 28948400.0 30977000 6
245 9551980.0 9572840 15
[6 rows x 58 columns]
Outliers in p10u_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
97 CHINA 22.597144 114.543139 615931000 702252000 758819000
121 JAPAN 36.458461 140.606342 150088000 153878000 155325000
147 CHINA 22.606110 114.553247 616314000 702669000 759257000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
237 CHINA 21.917778 112.981944 575483000 653428000 707083000
245 JAPAN 36.466624 140.609604 150073000 153861000 155307000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
97 314938000.0 362457000.0 390888000.0 300993000 ... 64757000.0
121 116253000.0 119213000.0 120223000.0 33834900 ... 52772100.0
147 315206000.0 362753000.0 391203000.0 301107000 ... 64798900.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
237 272990000.0 314491000.0 339614000.0 302493000 ... 61722200.0
245 116229000.0 119186000.0 120195000.0 33843900 ... 52762100.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
97 85134500.0 91288100.0 44852500.0 58674900.0 62971100.0 19904500.0
121 55009400.0 55137900.0 43514200.0 45459400.0 45567000.0 9257910.0
147 85178800.0 91335400.0 44873900.0 58697000.0 62994700.0 19925000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
237 80251900.0 86074100.0 39459400.0 51303500.0 55097200.0 22262800.0
245 54998500.0 55127000.0 43501900.0 45446600.0 45554200.0 9260260.0
p00r_300 p10r_300 Country_encoded
97 26459600.0 28317000 6
121 9550020.0 9570870 15
147 26481800.0 28340700 6
167 103177000.0 120268000 12
201 37271400.0 39811200 6
237 28948400.0 30977000 6
245 9551980.0 9572840 15
[7 rows x 58 columns]
Outliers in p90r_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
167 103177000.0 120268000 12
201 37271400.0 39811200 6
[3 rows x 58 columns]
Outliers in p00r_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
123 48695900.0 56664800 12
167 103177000.0 120268000 12
[3 rows x 58 columns]
Outliers in p10r_150:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
39 CHINA 39.740929 116.030139 701332000 777851000 829594000
43 PAKISTAN 32.390929 71.463095 424183000 546171000 651723000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
39 393377000.0 436918000.0 465857000.0 307954000 ... 81160100.0
43 131066000.0 169058000.0 200907000.0 293117000 ... 70198600.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
39 91306200.0 97528200.0 47571700.0 53381900.0 57023100.0 33588400.0
43 89264100.0 111771000.0 21823700.0 27781300.0 34699400.0 48374900.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
p00r_300 p10r_300 Country_encoded
39 37924300.0 40505100 6
43 61482800.0 77071200 21
123 48695900.0 56664800 12
167 103177000.0 120268000 12
[4 rows x 58 columns]
Outliers in p90_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
167 103177000.0 120268000 12
243 47354800.0 50583400 6
[3 rows x 58 columns]
Outliers in p00_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[4 rows x 58 columns]
Outliers in p10_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[4 rows x 58 columns]
Outliers in p90u_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
243 47354800.0 50583400 6
[2 rows x 58 columns]
Outliers in p00u_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
243 47354800.0 50583400 6
[2 rows x 58 columns]
Outliers in p10u_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
243 47354800.0 50583400 6
[2 rows x 58 columns]
Outliers in p90r_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
101 CHINA 36.708333 121.383333 742392000 820894000 873598000
153 INDIA 12.553056 80.173333 356322000 421981000 489751000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
101 431762000.0 476751000.0 507009000.0 310629000 ... 36147200.0
153 115092000.0 137358000.0 159491000.0 241229000 ... 48114200.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
101 39052100.0 41715800.0 20213900.0 21771800.0 23258100.0 15933300.0
153 55720800.0 64848800.0 19946200.0 23014700.0 26796200.0 28168000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
101 17280300.0 18457700 6
153 32706100.0 38052600 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[5 rows x 58 columns]
Outliers in p00r_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
43 PAKISTAN 32.390929 71.463095 424183000 546171000 651723000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
153 INDIA 12.553056 80.173333 356322000 421981000 489751000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
43 131066000.0 169058000.0 200907000.0 293117000 ... 70198600.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
153 115092000.0 137358000.0 159491000.0 241229000 ... 48114200.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
43 89264100.0 111771000.0 21823700.0 27781300.0 34699400.0 48374900.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
153 55720800.0 64848800.0 19946200.0 23014700.0 26796200.0 28168000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
43 61482800.0 77071200 21
123 48695900.0 56664800 12
153 32706100.0 38052600 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[6 rows x 58 columns]
Outliers in p10r_600:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
43 PAKISTAN 32.390929 71.463095 424183000 546171000 651723000
122 INDIA 14.865026 74.438709 411477000 487089000 565595000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
153 INDIA 12.553056 80.173333 356322000 421981000 489751000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
43 131066000.0 169058000.0 200907000.0 293117000 ... 70198600.0
122 137096000.0 163614000.0 190060000.0 274382000 ... 35497700.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
153 115092000.0 137358000.0 159491000.0 241229000 ... 48114200.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
43 89264100.0 111771000.0 21823700.0 27781300.0 34699400.0 48374900.0
122 43529800.0 50642200.0 9658560.0 11757800.0 13680800.0 25839200.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
153 55720800.0 64848800.0 19946200.0 23014700.0 26796200.0 28168000.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
43 61482800.0 77071200 21
122 31772000.0 36961400 12
123 48695900.0 56664800 12
153 32706100.0 38052600 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[7 rows x 58 columns]
Outliers in p90_300:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
167 103177000.0 120268000 12
243 47354800.0 50583400 6
[2 rows x 58 columns]
Outliers in p00_300:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
167 103177000.0 120268000 12
201 37271400.0 39811200 6
243 47354800.0 50583400 6
[3 rows x 58 columns]
Outliers in p10_300:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
201 CHINA 30.435681 120.947735 808445000 906681000 966557000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
201 485750000.0 546473000.0 582459000.0 322695000 ... 93688800.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
201 105361000.0 112549000.0 60547000.0 68089300.0 72737400.0 33141900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
167 103177000.0 120268000 12
201 37271400.0 39811200 6
243 47354800.0 50583400 6
[3 rows x 58 columns]
Outliers in p90u_300: Empty DataFrame Columns: [Country, Latitude, Longitude, p90_1200, p00_1200, p10_1200, p90u_1200, p00u_1200, p10u_1200, p90r_1200, p00r_1200, p10r_1200, p90_30, p00_30, p10_30, p90u_30, p00u_30, p10u_30, p90r_30, p00r_30, p10r_30, p90_75, p00_75, p10_75, p90u_75, p00u_75, p10u_75, p90r_75, p00r_75, p10r_75, p90_150, p00_150, p10_150, p90u_150, p00u_150, p10u_150, p90r_150, p00r_150, p10r_150, p90_600, p00_600, p10_600, p90u_600, p00u_600, p10u_600, p90r_600, p00r_600, p10r_600, p90_300, p00_300, p10_300, p90u_300, p00u_300, p10u_300, p90r_300, p00r_300, p10r_300, Country_encoded] Index: [] [0 rows x 58 columns]
Outliers in p00u_300: Empty DataFrame Columns: [Country, Latitude, Longitude, p90_1200, p00_1200, p10_1200, p90u_1200, p00u_1200, p10u_1200, p90r_1200, p00r_1200, p10r_1200, p90_30, p00_30, p10_30, p90u_30, p00u_30, p10u_30, p90r_30, p00r_30, p10r_30, p90_75, p00_75, p10_75, p90u_75, p00u_75, p10u_75, p90r_75, p00r_75, p10r_75, p90_150, p00_150, p10_150, p90u_150, p00u_150, p10u_150, p90r_150, p00r_150, p10r_150, p90_600, p00_600, p10_600, p90u_600, p00u_600, p10u_600, p90r_600, p00r_600, p10r_600, p90_300, p00_300, p10_300, p90u_300, p00u_300, p10u_300, p90r_300, p00r_300, p10r_300, Country_encoded] Index: [] [0 rows x 58 columns]
Outliers in p10u_300: Empty DataFrame Columns: [Country, Latitude, Longitude, p90_1200, p00_1200, p10_1200, p90u_1200, p00u_1200, p10u_1200, p90r_1200, p00r_1200, p10r_1200, p90_30, p00_30, p10_30, p90u_30, p00u_30, p10u_30, p90r_30, p00r_30, p10r_30, p90_75, p00_75, p10_75, p90u_75, p00u_75, p10u_75, p90r_75, p00r_75, p10r_75, p90_150, p00_150, p10_150, p90u_150, p00u_150, p10u_150, p90r_150, p00r_150, p10r_150, p90_600, p00_600, p10_600, p90u_600, p00u_600, p10u_600, p90r_600, p00r_600, p10r_600, p90_300, p00_300, p10_300, p90u_300, p00u_300, p10u_300, p90r_300, p00r_300, p10r_300, Country_encoded] Index: [] [0 rows x 58 columns]
Outliers in p90r_300:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
43 PAKISTAN 32.390929 71.463095 424183000 546171000 651723000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
43 131066000.0 169058000.0 200907000.0 293117000 ... 70198600.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
43 89264100.0 111771000.0 21823700.0 27781300.0 34699400.0 48374900.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
43 61482800.0 77071200 21
123 48695900.0 56664800 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[5 rows x 58 columns]
Outliers in p00r_300:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
43 PAKISTAN 32.390929 71.463095 424183000 546171000 651723000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
43 131066000.0 169058000.0 200907000.0 293117000 ... 70198600.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
43 89264100.0 111771000.0 21823700.0 27781300.0 34699400.0 48374900.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
43 61482800.0 77071200 21
123 48695900.0 56664800 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[5 rows x 58 columns]
Outliers in p10r_300:
Country Latitude Longitude p90_1200 p00_1200 p10_1200 \
43 PAKISTAN 32.390929 71.463095 424183000 546171000 651723000
123 INDIA 21.236525 73.350193 658974000 816024000 958281000
167 INDIA 28.159867 78.408658 818999000 1007240000 1188970000
204 INDIA 24.872911 75.620019 780956000 957012000 1128870000
243 CHINA 34.687468 119.459851 826843000 914475000 974481000
p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
43 131066000.0 169058000.0 200907000.0 293117000 ... 70198600.0
123 204556000.0 256667000.0 301941000.0 454417000 ... 74280500.0
167 218150000.0 274801000.0 324681000.0 600849000 ... 115482000.0
204 214412000.0 269312000.0 317973000.0 566544000 ... 55657000.0
243 475506000.0 526671000.0 561015000.0 351337000 ... 106586000.0
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 \
43 89264100.0 111771000.0 21823700.0 27781300.0 34699400.0 48374900.0
123 93957100.0 109390000.0 35411200.0 45261200.0 52725300.0 38869300.0
167 153113000.0 178411000.0 36030100.0 49936000.0 58143700.0 79451800.0
204 64985200.0 75634600.0 14781100.0 16868100.0 19637700.0 40875900.0
243 115666000.0 123553000.0 62974600.0 68311400.0 72969700.0 43611600.0
p00r_300 p10r_300 Country_encoded
43 61482800.0 77071200 21
123 48695900.0 56664800 12
167 103177000.0 120268000 12
204 48117100.0 55996900 12
243 47354800.0 50583400 6
[5 rows x 58 columns]
# Select the columns you want to standardize
column_standardize = ['Country_encoded', 'Latitude', 'Longitude', 'p90_1200', 'p00_1200', 'p10_1200', 'p90u_1200', 'p00u_1200', 'p10u_1200', 'p90r_1200', 'p00r_1200', 'p10r_1200', 'p90_30', 'p00_30', 'p10_30', 'p90u_30', 'p00u_30', 'p10u_30', 'p90r_30', 'p00r_30', 'p10r_30', 'p90_75', 'p00_75', 'p10_75', 'p90u_75', 'p00u_75', 'p10u_75', 'p90r_75', 'p00r_75', 'p10r_75', 'p90_150', 'p00_150', 'p10_150', 'p90u_150', 'p00u_150', 'p10u_150', 'p90r_150', 'p00r_150', 'p10r_150', 'p90_600', 'p00_600', 'p10_600', 'p90u_600', 'p00u_600', 'p10u_600', 'p90r_600', 'p00r_600', 'p10r_600', 'p90_300', 'p00_300', 'p10_300', 'p90u_300', 'p00u_300', 'p10u_300', 'p90r_300', 'p00r_300', 'p10r_300']
# Create a StandardScaler object
scaler = StandardScaler()
# Fit the scaler to the selected columns
scaler.fit(df[column_standardize])
# Transform the selected columns by applying standardization
df[column_standardize] = scaler.transform(df[column_standardize])
df[column_standardize]
| Country_encoded | Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | p90u_1200 | p00u_1200 | p10u_1200 | p90r_1200 | ... | p10r_600 | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.605681 | 1.352765 | 0.251194 | -0.464402 | -0.508016 | -0.554848 | -0.593107 | -0.660152 | -0.734917 | -0.252291 | ... | -0.599107 | -1.172443 | -1.136296 | -1.125151 | -1.191514 | -1.198046 | -1.215751 | -0.738981 | -0.675829 | -0.636833 |
| 1 | 0.514631 | -0.126329 | -0.064588 | -0.774040 | -0.731805 | -0.679515 | -0.964721 | -0.953322 | -0.919337 | -0.444835 | ... | -0.317110 | -0.586885 | -0.600261 | -0.556108 | -0.716401 | -0.736024 | -0.708998 | -0.154835 | -0.193095 | -0.156917 |
| 2 | -1.670572 | -4.916056 | -0.579314 | -1.002907 | -0.916580 | -0.857975 | -1.183329 | -1.120005 | -1.079853 | -0.644420 | ... | -0.339928 | 0.414370 | 0.496365 | 0.605076 | 0.653952 | 0.779507 | 0.935261 | -0.156248 | -0.111894 | -0.068467 |
| 3 | 1.060932 | -0.469286 | -1.226995 | -0.889115 | -0.813688 | -0.764634 | -0.908713 | -0.841270 | -0.801030 | -0.714629 | ... | -0.584963 | -1.145335 | -1.094991 | -1.071174 | -1.169357 | -1.162423 | -1.166418 | -0.712229 | -0.638664 | -0.593155 |
| 4 | 0.514631 | -0.020197 | 0.018589 | 0.051419 | 0.029799 | 0.051246 | 0.176309 | 0.148003 | 0.179467 | -0.085040 | ... | -0.367127 | -0.741186 | -0.728155 | -0.685837 | -0.701982 | -0.714859 | -0.682794 | -0.559051 | -0.517095 | -0.473250 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | -1.397422 | -1.506439 | 1.501828 | 1.792834 | 1.899641 | 1.913771 | 0.839405 | 1.051898 | 1.110167 | 2.454943 | ... | 1.483419 | 1.727114 | 2.251499 | 2.276462 | 1.196198 | 1.746700 | 1.828051 | 2.090747 | 2.335818 | 2.210780 |
| 272 | 1.060932 | 0.096301 | -0.957393 | -0.854920 | -0.820254 | -0.771264 | -0.789761 | -0.786267 | -0.743154 | -0.772925 | ... | -0.572764 | 0.245594 | 0.188036 | 0.253678 | 0.620326 | 0.569365 | 0.671899 | -0.509843 | -0.477951 | -0.437206 |
| 273 | -0.395870 | -0.461599 | 1.689799 | 2.357024 | 2.340021 | 2.270520 | 2.538004 | 2.634711 | 2.644594 | 1.762702 | ... | 0.120417 | 0.566912 | 0.570582 | 0.541617 | 0.867854 | 0.941671 | 0.931923 | -0.165667 | -0.201114 | -0.199622 |
| 274 | 0.878832 | 0.461080 | 0.470339 | 0.061055 | -0.037393 | -0.131383 | -0.141744 | -0.234249 | -0.340844 | 0.257537 | ... | -0.223553 | -0.455104 | -0.551699 | -0.640980 | -0.537094 | -0.643647 | -0.744355 | -0.153133 | -0.229645 | -0.287221 |
| 275 | 1.060932 | 0.074844 | -1.154910 | -0.616189 | -0.577300 | -0.524737 | -0.479518 | -0.452401 | -0.391292 | -0.648693 | ... | -0.535978 | -0.497452 | -0.464913 | -0.420298 | -0.360175 | -0.330085 | -0.282576 | -0.574150 | -0.530945 | -0.488370 |
276 rows × 57 columns
#correlation
df.corr()
C:\Users\prabha\AppData\Local\Temp\ipykernel_18132\930112212.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning. df.corr()
| Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | p90u_1200 | p00u_1200 | p10u_1200 | p90r_1200 | p00r_1200 | ... | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | Country_encoded | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Latitude | 1.000000 | -0.042836 | -0.009781 | -0.073953 | -0.111928 | 0.156477 | 0.090043 | 0.053836 | -0.177858 | -0.215616 | ... | 0.012607 | -0.045970 | -0.078337 | 0.082410 | 0.031985 | 0.005220 | -0.116827 | -0.155200 | -0.175544 | 0.084602 |
| Longitude | -0.042836 | 1.000000 | 0.593553 | 0.587779 | 0.567162 | 0.503450 | 0.514429 | 0.498042 | 0.582437 | 0.560700 | ... | 0.448198 | 0.446263 | 0.426163 | 0.354557 | 0.361703 | 0.341938 | 0.463441 | 0.438351 | 0.414278 | -0.549427 |
| p90_1200 | -0.009781 | 0.593553 | 1.000000 | 0.993697 | 0.981456 | 0.915903 | 0.940142 | 0.947505 | 0.912134 | 0.881890 | ... | 0.683437 | 0.705045 | 0.703963 | 0.503745 | 0.537621 | 0.541605 | 0.772836 | 0.746307 | 0.718247 | -0.552493 |
| p00_1200 | -0.073953 | 0.587779 | 0.993697 | 1.000000 | 0.996458 | 0.874553 | 0.909984 | 0.924483 | 0.942714 | 0.921350 | ... | 0.671828 | 0.705215 | 0.712202 | 0.476288 | 0.518611 | 0.528324 | 0.793592 | 0.776905 | 0.755299 | -0.529692 |
| p10_1200 | -0.111928 | 0.567162 | 0.981456 | 0.996458 | 1.000000 | 0.838057 | 0.880295 | 0.900355 | 0.957368 | 0.942899 | ... | 0.662495 | 0.703799 | 0.717241 | 0.455220 | 0.502707 | 0.516957 | 0.808476 | 0.798964 | 0.782695 | -0.510042 |
| p90u_1200 | 0.156477 | 0.503450 | 0.915903 | 0.874553 | 0.838057 | 1.000000 | 0.994082 | 0.984650 | 0.670895 | 0.619903 | ... | 0.655884 | 0.636550 | 0.611634 | 0.584574 | 0.589668 | 0.579526 | 0.560367 | 0.508081 | 0.464968 | -0.518746 |
| p00u_1200 | 0.090043 | 0.514429 | 0.940142 | 0.909984 | 0.880295 | 0.994082 | 1.000000 | 0.997322 | 0.721719 | 0.677228 | ... | 0.660659 | 0.652715 | 0.634439 | 0.573294 | 0.587676 | 0.582786 | 0.592297 | 0.547947 | 0.509093 | -0.510720 |
| p10u_1200 | 0.053836 | 0.498042 | 0.947505 | 0.924483 | 0.900355 | 0.984650 | 0.997322 | 1.000000 | 0.744952 | 0.705466 | ... | 0.662244 | 0.661272 | 0.648351 | 0.565323 | 0.585009 | 0.584451 | 0.610473 | 0.571614 | 0.536482 | -0.499197 |
| p90r_1200 | -0.177858 | 0.582437 | 0.912134 | 0.942714 | 0.957368 | 0.670895 | 0.721719 | 0.744952 | 1.000000 | 0.996198 | ... | 0.592830 | 0.652492 | 0.675936 | 0.333685 | 0.391065 | 0.408782 | 0.855526 | 0.859906 | 0.852093 | -0.490963 |
| p00r_1200 | -0.215616 | 0.560700 | 0.881890 | 0.921350 | 0.942899 | 0.619903 | 0.677228 | 0.705466 | 0.996198 | 1.000000 | ... | 0.572753 | 0.639449 | 0.668980 | 0.307685 | 0.369304 | 0.391125 | 0.852904 | 0.864876 | 0.862962 | -0.461099 |
| p10r_1200 | -0.238073 | 0.535896 | 0.852854 | 0.898521 | 0.925566 | 0.575487 | 0.636644 | 0.668593 | 0.987911 | 0.997540 | ... | 0.555958 | 0.627389 | 0.661602 | 0.286079 | 0.350105 | 0.374943 | 0.850451 | 0.868009 | 0.870772 | -0.437276 |
| p90_30 | -0.042807 | 0.278141 | 0.390220 | 0.398820 | 0.397571 | 0.361934 | 0.383573 | 0.390973 | 0.351306 | 0.348093 | ... | 0.342201 | 0.353131 | 0.350017 | 0.314624 | 0.334661 | 0.337283 | 0.275103 | 0.269882 | 0.257849 | -0.156847 |
| p00_30 | -0.071382 | 0.272715 | 0.395847 | 0.410268 | 0.413002 | 0.349772 | 0.376796 | 0.387706 | 0.374122 | 0.374761 | ... | 0.337559 | 0.356699 | 0.357316 | 0.300235 | 0.327166 | 0.332768 | 0.289517 | 0.289894 | 0.280089 | -0.153498 |
| p10_30 | -0.091969 | 0.261762 | 0.385404 | 0.404440 | 0.410763 | 0.327720 | 0.358283 | 0.371956 | 0.377348 | 0.381776 | ... | 0.319007 | 0.342038 | 0.346256 | 0.277772 | 0.307134 | 0.315436 | 0.284293 | 0.288444 | 0.281686 | -0.139111 |
| p90u_30 | -0.025076 | 0.202648 | 0.262994 | 0.269027 | 0.266086 | 0.263968 | 0.280668 | 0.285346 | 0.216306 | 0.214256 | ... | 0.211601 | 0.212181 | 0.206587 | 0.225596 | 0.235222 | 0.235816 | 0.114451 | 0.107904 | 0.098541 | -0.073771 |
| p00u_30 | -0.048304 | 0.197067 | 0.265332 | 0.275863 | 0.275960 | 0.253946 | 0.274822 | 0.282248 | 0.230859 | 0.231867 | ... | 0.204362 | 0.210474 | 0.207392 | 0.212824 | 0.227324 | 0.230066 | 0.119596 | 0.116580 | 0.108661 | -0.070419 |
| p10u_30 | -0.065892 | 0.187799 | 0.255588 | 0.269769 | 0.272688 | 0.235632 | 0.259306 | 0.268926 | 0.231560 | 0.235601 | ... | 0.187099 | 0.196002 | 0.195585 | 0.193482 | 0.209781 | 0.214621 | 0.111940 | 0.111605 | 0.105901 | -0.059179 |
| p90r_30 | -0.091113 | 0.421084 | 0.682476 | 0.696501 | 0.703346 | 0.546776 | 0.575516 | 0.589791 | 0.702471 | 0.696355 | ... | 0.680388 | 0.728709 | 0.738298 | 0.491953 | 0.543683 | 0.553320 | 0.786499 | 0.790399 | 0.774745 | -0.411759 |
| p00r_30 | -0.117985 | 0.400524 | 0.664460 | 0.685194 | 0.696747 | 0.508891 | 0.543169 | 0.561031 | 0.707875 | 0.706620 | ... | 0.654482 | 0.713562 | 0.728623 | 0.457503 | 0.516960 | 0.530431 | 0.784732 | 0.798480 | 0.787424 | -0.387928 |
| p10r_30 | -0.136154 | 0.386479 | 0.653287 | 0.679280 | 0.695131 | 0.481798 | 0.519890 | 0.540839 | 0.714900 | 0.717950 | ... | 0.639250 | 0.703954 | 0.724050 | 0.433494 | 0.496047 | 0.512797 | 0.790424 | 0.809901 | 0.803366 | -0.369033 |
| p90_75 | -0.089833 | 0.290413 | 0.494629 | 0.504149 | 0.505120 | 0.440615 | 0.466112 | 0.477876 | 0.463846 | 0.457601 | ... | 0.588741 | 0.613657 | 0.613717 | 0.545132 | 0.584054 | 0.594746 | 0.466427 | 0.465026 | 0.447212 | -0.257120 |
| p00_75 | -0.125558 | 0.282451 | 0.497924 | 0.514842 | 0.520680 | 0.419051 | 0.451512 | 0.467409 | 0.491956 | 0.490267 | ... | 0.568476 | 0.605787 | 0.610878 | 0.508644 | 0.557429 | 0.571629 | 0.482146 | 0.489473 | 0.474878 | -0.250862 |
| p10_75 | -0.149335 | 0.269202 | 0.490433 | 0.512592 | 0.522592 | 0.396990 | 0.433616 | 0.452825 | 0.500642 | 0.503052 | ... | 0.552840 | 0.595212 | 0.604845 | 0.485971 | 0.537956 | 0.555543 | 0.484449 | 0.496410 | 0.485430 | -0.233543 |
| p90u_75 | -0.069933 | 0.193839 | 0.348977 | 0.355197 | 0.353557 | 0.335294 | 0.355842 | 0.364899 | 0.302318 | 0.296675 | ... | 0.449885 | 0.464933 | 0.461427 | 0.469045 | 0.499679 | 0.509164 | 0.262329 | 0.261460 | 0.245716 | -0.159453 |
| p00u_75 | -0.101832 | 0.189903 | 0.354118 | 0.366118 | 0.368009 | 0.321228 | 0.347575 | 0.359835 | 0.326178 | 0.323806 | ... | 0.431643 | 0.456767 | 0.456650 | 0.438503 | 0.477678 | 0.489641 | 0.272349 | 0.277886 | 0.263982 | -0.158670 |
| p10u_75 | -0.122215 | 0.177409 | 0.345034 | 0.361059 | 0.366094 | 0.302142 | 0.331730 | 0.346565 | 0.328885 | 0.329683 | ... | 0.414566 | 0.443150 | 0.446317 | 0.418013 | 0.459435 | 0.474019 | 0.267207 | 0.275960 | 0.264639 | -0.142690 |
| p90r_75 | -0.107191 | 0.448397 | 0.703960 | 0.719068 | 0.727788 | 0.549890 | 0.578077 | 0.592412 | 0.738981 | 0.733992 | ... | 0.728898 | 0.772337 | 0.783635 | 0.509052 | 0.554405 | 0.563481 | 0.874802 | 0.872412 | 0.857091 | -0.434870 |
| p00r_75 | -0.134632 | 0.421512 | 0.684287 | 0.707621 | 0.722479 | 0.505640 | 0.540367 | 0.559310 | 0.747822 | 0.749038 | ... | 0.698500 | 0.754025 | 0.772329 | 0.466688 | 0.520151 | 0.534016 | 0.876208 | 0.885273 | 0.875878 | -0.404121 |
| p10r_75 | -0.152810 | 0.402159 | 0.668005 | 0.696889 | 0.716396 | 0.473309 | 0.511908 | 0.534159 | 0.750758 | 0.756674 | ... | 0.677438 | 0.738747 | 0.762515 | 0.437371 | 0.493851 | 0.511275 | 0.877116 | 0.892386 | 0.888040 | -0.381498 |
| p90_150 | -0.078705 | 0.383489 | 0.498071 | 0.499282 | 0.496760 | 0.457713 | 0.471595 | 0.476610 | 0.452746 | 0.443829 | ... | 0.808004 | 0.813821 | 0.805575 | 0.773159 | 0.796794 | 0.800752 | 0.595307 | 0.581380 | 0.557702 | -0.358007 |
| p00_150 | -0.121544 | 0.375054 | 0.520748 | 0.531776 | 0.536025 | 0.443795 | 0.467185 | 0.478155 | 0.508852 | 0.505629 | ... | 0.796680 | 0.820111 | 0.819651 | 0.733034 | 0.770332 | 0.779727 | 0.639474 | 0.637715 | 0.618573 | -0.352651 |
| p10_150 | -0.147272 | 0.355924 | 0.522420 | 0.539637 | 0.548932 | 0.426676 | 0.455277 | 0.470538 | 0.529421 | 0.530741 | ... | 0.786982 | 0.817871 | 0.823582 | 0.710949 | 0.753224 | 0.767324 | 0.655283 | 0.659817 | 0.645107 | -0.334995 |
| p90u_150 | -0.050610 | 0.295709 | 0.328158 | 0.322101 | 0.313866 | 0.351819 | 0.356897 | 0.356464 | 0.246981 | 0.236963 | ... | 0.691987 | 0.679992 | 0.663645 | 0.746001 | 0.755851 | 0.756108 | 0.359498 | 0.342604 | 0.318644 | -0.256568 |
| p00u_150 | -0.089724 | 0.294465 | 0.357470 | 0.359223 | 0.356044 | 0.351899 | 0.365227 | 0.369677 | 0.301051 | 0.295030 | ... | 0.695414 | 0.698221 | 0.687508 | 0.726595 | 0.748819 | 0.753435 | 0.402693 | 0.395166 | 0.373700 | -0.260056 |
| p10u_150 | -0.112548 | 0.275048 | 0.359229 | 0.365703 | 0.366302 | 0.341098 | 0.358716 | 0.366706 | 0.315330 | 0.312632 | ... | 0.689454 | 0.697963 | 0.691899 | 0.714137 | 0.740600 | 0.749300 | 0.410411 | 0.407643 | 0.389150 | -0.244000 |
| p90r_150 | -0.117169 | 0.445536 | 0.721368 | 0.740618 | 0.753745 | 0.534640 | 0.565129 | 0.581931 | 0.786713 | 0.784373 | ... | 0.762769 | 0.811600 | 0.827516 | 0.515817 | 0.564655 | 0.576388 | 0.945732 | 0.945264 | 0.932310 | -0.465686 |
| p00r_150 | -0.147858 | 0.416005 | 0.695123 | 0.723150 | 0.742765 | 0.484330 | 0.521791 | 0.543482 | 0.789603 | 0.794011 | ... | 0.723758 | 0.785402 | 0.808567 | 0.467564 | 0.525080 | 0.541814 | 0.936575 | 0.948680 | 0.942170 | -0.429625 |
| p10r_150 | -0.165813 | 0.394212 | 0.673938 | 0.707648 | 0.732051 | 0.448201 | 0.489486 | 0.514540 | 0.787358 | 0.796789 | ... | 0.697431 | 0.764559 | 0.793337 | 0.434420 | 0.494539 | 0.514863 | 0.931435 | 0.949895 | 0.948872 | -0.402909 |
| p90_600 | 0.076954 | 0.445624 | 0.843624 | 0.820751 | 0.804664 | 0.822802 | 0.822563 | 0.822873 | 0.718312 | 0.685215 | ... | 0.865318 | 0.854707 | 0.841665 | 0.735396 | 0.745268 | 0.742552 | 0.803555 | 0.756093 | 0.720038 | -0.559132 |
| p00_600 | 0.014709 | 0.451663 | 0.863248 | 0.852601 | 0.844762 | 0.802299 | 0.813779 | 0.821253 | 0.775502 | 0.749968 | ... | 0.863481 | 0.867144 | 0.862588 | 0.709083 | 0.729632 | 0.732838 | 0.846222 | 0.809181 | 0.779070 | -0.551341 |
| p10_600 | -0.020343 | 0.433592 | 0.859790 | 0.857548 | 0.856500 | 0.774521 | 0.792916 | 0.805978 | 0.797480 | 0.778304 | ... | 0.854128 | 0.866162 | 0.868737 | 0.685258 | 0.711227 | 0.719475 | 0.865996 | 0.836200 | 0.811760 | -0.532534 |
| p90u_600 | 0.198119 | 0.342015 | 0.681404 | 0.633832 | 0.600762 | 0.801413 | 0.777294 | 0.764457 | 0.440467 | 0.395981 | ... | 0.828019 | 0.782108 | 0.748807 | 0.823624 | 0.808715 | 0.795026 | 0.553918 | 0.490431 | 0.444374 | -0.485486 |
| p00u_600 | 0.147573 | 0.354976 | 0.718142 | 0.678759 | 0.650654 | 0.812509 | 0.797710 | 0.790220 | 0.497006 | 0.456562 | ... | 0.845781 | 0.810137 | 0.782014 | 0.824353 | 0.818288 | 0.808881 | 0.596168 | 0.538855 | 0.495329 | -0.491781 |
| p10u_600 | 0.121725 | 0.335228 | 0.724191 | 0.690346 | 0.666795 | 0.805892 | 0.796343 | 0.793384 | 0.514937 | 0.478404 | ... | 0.848104 | 0.817994 | 0.794808 | 0.819094 | 0.817201 | 0.812011 | 0.611291 | 0.558423 | 0.518183 | -0.479169 |
| p90r_600 | -0.116411 | 0.474364 | 0.849645 | 0.868109 | 0.880540 | 0.633530 | 0.667412 | 0.686391 | 0.922714 | 0.914701 | ... | 0.687381 | 0.729949 | 0.749285 | 0.413130 | 0.455710 | 0.469367 | 0.944956 | 0.933026 | 0.920867 | -0.514817 |
| p00r_600 | -0.158411 | 0.458346 | 0.825450 | 0.854177 | 0.874190 | 0.582275 | 0.624287 | 0.648904 | 0.930355 | 0.930413 | ... | 0.663231 | 0.716049 | 0.742704 | 0.379200 | 0.428367 | 0.446821 | 0.946566 | 0.944921 | 0.939678 | -0.484983 |
| p10r_600 | -0.182044 | 0.437295 | 0.797284 | 0.832764 | 0.858436 | 0.537779 | 0.584269 | 0.612792 | 0.923757 | 0.929932 | ... | 0.640775 | 0.699237 | 0.731425 | 0.351110 | 0.403125 | 0.425036 | 0.941858 | 0.946870 | 0.947306 | -0.457815 |
| p90_300 | 0.012607 | 0.448198 | 0.683437 | 0.671828 | 0.662495 | 0.655884 | 0.660659 | 0.662244 | 0.592830 | 0.572753 | ... | 1.000000 | 0.990770 | 0.977804 | 0.935726 | 0.950012 | 0.950329 | 0.774680 | 0.739618 | 0.708504 | -0.456634 |
| p00_300 | -0.045970 | 0.446263 | 0.705045 | 0.705215 | 0.703799 | 0.636550 | 0.652715 | 0.661272 | 0.652492 | 0.639449 | ... | 0.990770 | 1.000000 | 0.996047 | 0.897112 | 0.925717 | 0.932376 | 0.821271 | 0.799186 | 0.773820 | -0.451601 |
| p10_300 | -0.078337 | 0.426163 | 0.703963 | 0.712202 | 0.717241 | 0.611634 | 0.634439 | 0.648351 | 0.675936 | 0.668980 | ... | 0.977804 | 0.996047 | 1.000000 | 0.868113 | 0.902519 | 0.914888 | 0.841464 | 0.827076 | 0.807827 | -0.430609 |
| p90u_300 | 0.082410 | 0.354557 | 0.503745 | 0.476288 | 0.455220 | 0.584574 | 0.573294 | 0.565323 | 0.333685 | 0.307685 | ... | 0.935726 | 0.897112 | 0.868113 | 1.000000 | 0.993769 | 0.986514 | 0.501838 | 0.457438 | 0.420541 | -0.353348 |
| p00u_300 | 0.031985 | 0.361703 | 0.537621 | 0.518611 | 0.502707 | 0.589668 | 0.587676 | 0.585009 | 0.391065 | 0.369304 | ... | 0.950012 | 0.925717 | 0.902519 | 0.993769 | 1.000000 | 0.997512 | 0.548043 | 0.512479 | 0.478237 | -0.360308 |
| p10u_300 | 0.005220 | 0.341938 | 0.541605 | 0.528324 | 0.516957 | 0.579526 | 0.582786 | 0.584451 | 0.408782 | 0.391125 | ... | 0.950329 | 0.932376 | 0.914888 | 0.986514 | 0.997512 | 1.000000 | 0.561826 | 0.531552 | 0.501118 | -0.342843 |
| p90r_300 | -0.116827 | 0.463441 | 0.772836 | 0.793592 | 0.808476 | 0.560367 | 0.592297 | 0.610473 | 0.855526 | 0.852904 | ... | 0.774680 | 0.821271 | 0.841464 | 0.501838 | 0.548043 | 0.561826 | 1.000000 | 0.993620 | 0.983469 | -0.486294 |
| p00r_300 | -0.155200 | 0.438351 | 0.746307 | 0.776905 | 0.798964 | 0.508081 | 0.547947 | 0.571614 | 0.859906 | 0.864876 | ... | 0.739618 | 0.799186 | 0.827076 | 0.457438 | 0.512479 | 0.531552 | 0.993620 | 1.000000 | 0.996828 | -0.452686 |
| p10r_300 | -0.175544 | 0.414278 | 0.718247 | 0.755299 | 0.782695 | 0.464968 | 0.509093 | 0.536482 | 0.852093 | 0.862962 | ... | 0.708504 | 0.773820 | 0.807827 | 0.420541 | 0.478237 | 0.501118 | 0.983469 | 0.996828 | 1.000000 | -0.422487 |
| Country_encoded | 0.084602 | -0.549427 | -0.552493 | -0.529692 | -0.510042 | -0.518746 | -0.510720 | -0.499197 | -0.490963 | -0.461099 | ... | -0.456634 | -0.451601 | -0.430609 | -0.353348 | -0.360308 | -0.342843 | -0.486294 | -0.452686 | -0.422487 | 1.000000 |
57 rows × 57 columns
# Step 2: Subset the data for relevant features
independent_features = ['p90_1200', 'p90u_1200', 'p90r_1200', 'p90_30', 'p90u_30', 'p90r_30', 'p90_75',
'p90u_75', 'p90r_75', 'p90_150', 'p90u_150', 'p90r_150', 'p90_600', 'p90u_600',
'p90r_600', 'p90_300', 'p90u_300', 'p90r_300']
dependent_features = ['p00_1200', 'p10_1200', 'p00u_1200', 'p10u_1200', 'p00r_1200', 'p10r_1200', 'p00_30',
'p10_30', 'p00u_30', 'p10u_30', 'p00r_30', 'p10r_30', 'p00_75', 'p10_75', 'p00u_75',
'p10u_75', 'p00r_75', 'p10r_75', 'p00_150', 'p10_150', 'p00u_150', 'p10u_150', 'p00r_150',
'p10r_150', 'p00_600', 'p10_600', 'p00u_600', 'p10u_600', 'p00r_600', 'p10r_600', 'p00_300',
'p10_300', 'p00u_300', 'p10u_300', 'p00r_300', 'p10r_300']
relevant_columns = independent_features + dependent_features
relevant_data = df[relevant_columns]
# Step 3: Data visualization
# Example 1: Box plot comparing independent features
plt.figure(figsize=(20, 12))
sns.boxplot(data=relevant_data[independent_features])
plt.title('Population Distribution - Independent Features')
plt.xticks(rotation=90)
plt.show()
# Compute the correlation matrix
correlation_matrix = df.corr()
# Set the dark background style
sns.set_style('dark')
# Create the heat map
plt.figure(figsize=(40,32))
sns.heatmap(correlation_matrix, cmap='coolwarm', annot=True, fmt='.2f')
plt.title('Correlation Heat Map')
plt.show()
C:\Users\prabha\AppData\Local\Temp\ipykernel_18132\3568341587.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning. correlation_matrix = df.corr()
import pandas as pd
# Print the first few rows of the DataFrame
print(df.head())
# List the column names of the DataFrame
print("Column names:", df.columns)
# Check the data types of the columns
print("Data types:", df.dtypes)
# Find the unique values in each column
for column in df.columns:
unique_values = df[column].unique()
print(f"Unique values in {column}:", unique_values)
Country Latitude Longitude p90_1200 p00_1200 \
0 SWEDEN 1.352765 0.251194 -0.464402 -0.508016
1 SPAIN -0.126329 -0.064588 -0.774040 -0.731805
2 BRAZIL -4.916056 -0.579314 -1.002907 -0.916580
3 UNITED STATES OF AMERICA -0.469286 -1.226995 -0.889115 -0.813688
4 SPAIN -0.020197 0.018589 0.051419 0.029799
p10_1200 p90u_1200 p00u_1200 p10u_1200 p90r_1200 ... p90_300 \
0 -0.554848 -0.593107 -0.660152 -0.734917 -0.252291 ... -1.172443
1 -0.679515 -0.964721 -0.953322 -0.919337 -0.444835 ... -0.586885
2 -0.857975 -1.183329 -1.120005 -1.079853 -0.644420 ... 0.414370
3 -0.764634 -0.908713 -0.841270 -0.801030 -0.714629 ... -1.145335
4 0.051246 0.176309 0.148003 0.179467 -0.085040 ... -0.741186
p00_300 p10_300 p90u_300 p00u_300 p10u_300 p90r_300 p00r_300 \
0 -1.136296 -1.125151 -1.191514 -1.198046 -1.215751 -0.738981 -0.675829
1 -0.600261 -0.556108 -0.716401 -0.736024 -0.708998 -0.154835 -0.193095
2 0.496365 0.605076 0.653952 0.779507 0.935261 -0.156248 -0.111894
3 -1.094991 -1.071174 -1.169357 -1.162423 -1.166418 -0.712229 -0.638664
4 -0.728155 -0.685837 -0.701982 -0.714859 -0.682794 -0.559051 -0.517095
p10r_300 Country_encoded
0 -0.636833 0.605681
1 -0.156917 0.514631
2 -0.068467 -1.670572
3 -0.593155 1.060932
4 -0.473250 0.514631
[5 rows x 58 columns]
Column names: Index(['Country', 'Latitude', 'Longitude', 'p90_1200', 'p00_1200', 'p10_1200',
'p90u_1200', 'p00u_1200', 'p10u_1200', 'p90r_1200', 'p00r_1200',
'p10r_1200', 'p90_30', 'p00_30', 'p10_30', 'p90u_30', 'p00u_30',
'p10u_30', 'p90r_30', 'p00r_30', 'p10r_30', 'p90_75', 'p00_75',
'p10_75', 'p90u_75', 'p00u_75', 'p10u_75', 'p90r_75', 'p00r_75',
'p10r_75', 'p90_150', 'p00_150', 'p10_150', 'p90u_150', 'p00u_150',
'p10u_150', 'p90r_150', 'p00r_150', 'p10r_150', 'p90_600', 'p00_600',
'p10_600', 'p90u_600', 'p00u_600', 'p10u_600', 'p90r_600', 'p00r_600',
'p10r_600', 'p90_300', 'p00_300', 'p10_300', 'p90u_300', 'p00u_300',
'p10u_300', 'p90r_300', 'p00r_300', 'p10r_300', 'Country_encoded'],
dtype='object')
Data types: Country object
Latitude float64
Longitude float64
p90_1200 float64
p00_1200 float64
p10_1200 float64
p90u_1200 float64
p00u_1200 float64
p10u_1200 float64
p90r_1200 float64
p00r_1200 float64
p10r_1200 float64
p90_30 float64
p00_30 float64
p10_30 float64
p90u_30 float64
p00u_30 float64
p10u_30 float64
p90r_30 float64
p00r_30 float64
p10r_30 float64
p90_75 float64
p00_75 float64
p10_75 float64
p90u_75 float64
p00u_75 float64
p10u_75 float64
p90r_75 float64
p00r_75 float64
p10r_75 float64
p90_150 float64
p00_150 float64
p10_150 float64
p90u_150 float64
p00u_150 float64
p10u_150 float64
p90r_150 float64
p00r_150 float64
p10r_150 float64
p90_600 float64
p00_600 float64
p10_600 float64
p90u_600 float64
p00u_600 float64
p10u_600 float64
p90r_600 float64
p00r_600 float64
p10r_600 float64
p90_300 float64
p00_300 float64
p10_300 float64
p90u_300 float64
p00u_300 float64
p10u_300 float64
p90r_300 float64
p00r_300 float64
p10r_300 float64
Country_encoded float64
dtype: object
Unique values in Country: ['SWEDEN' 'SPAIN' 'BRAZIL' 'UNITED STATES OF AMERICA' 'ARGENTINA'
'GERMANY' 'RUSSIAN FEDERATION' 'BULGARIA' 'FRANCE' 'UNITED KINGDOM'
'SWITZERLAND' 'KAZAKHSTAN' 'SLOVAK REPUBLIC' 'NETHERLANDS' 'CANADA'
'IRAN, ISLAMIC REPUBLIC OF' 'ITALY' 'CHINA' 'ROMANIA' 'PAKISTAN'
'UKRAINE' 'TAIWAN, CHINA' 'BELGIUM' 'CZECH REPUBLIC' 'JAPAN' 'LITHUANIA'
'INDIA' 'SOUTH AFRICA' 'KOREA, REPUBLIC OF' 'SLOVENIA' 'MEXICO' 'FINLAND'
'ARMENIA' 'HUNGARY']
Unique values in Latitude: [ 1.35276534e+00 -1.26329198e-01 -4.91605559e+00 -4.69285615e-01
-2.01966081e-02 -5.75176834e+00 7.19662906e-01 8.10391363e-01
1.08881949e+00 -6.42768222e-02 1.65048566e-01 4.60751238e-01
1.17311830e+00 7.79858133e-01 4.64155655e-01 6.28639209e-01
2.96919319e-01 2.02717020e+00 2.89066925e-01 1.63337513e-01
5.36005870e-01 -1.76126296e+00 7.59966221e-01 7.83585927e-01
-1.68721014e-02 5.25243619e-01 9.44431357e-01 -5.15502359e-01
2.18171743e-01 9.47544955e-01 -5.72377348e-01 3.30218600e-01
-9.63498625e-01 4.65222766e-02 -2.06376609e-01 -2.31051159e-01
2.75048563e-01 -4.89028305e-01 6.06091657e-01 -1.31450997e-01
2.17869259e-01 -1.68069194e+00 1.03324959e+00 -6.91889629e-01
7.56758377e-01 -1.23362219e+00 4.39641307e-01 6.57667261e-01
3.80576565e-01 -9.85893915e-02 -1.71423539e-01 3.81726417e-01
-6.98990729e-01 -8.41018622e-02 3.27376985e-01 2.41448170e-01
-9.53711994e-01 -5.49182052e-01 4.78014273e-01 1.83335488e-01
1.00899530e-02 -4.76805405e-01 7.95658842e-01 7.51857399e-01
3.89811364e-02 2.18212232e-01 1.30488924e+00 -5.73195393e-03
4.84742806e-02 5.81178902e-01 7.20488924e-01 2.92060888e-01
-5.61940966e+00 8.39465242e-01 3.80051344e-02 -1.51353315e+00
-7.80959645e-01 4.91167425e-01 1.57001125e-01 6.15409426e-01
1.44401893e+00 4.26444126e-03 -9.30579003e-02 -4.35421092e-01
-3.08297140e-01 -3.16334745e-01 -1.22128476e+00 -1.57500804e-02
-6.06049417e-01 3.75893204e-01 4.49945143e-01 2.01400064e-01
6.49591302e-01 -7.21126149e-01 7.28282529e-01 9.66525067e-01
8.05973811e-01 -1.43866724e+00 5.37702894e-01 -5.38293530e-01
1.30166527e-03 -3.62686909e-01 -6.90538943e-02 -5.21855750e-01
1.00421079e+00 -7.26715285e-01 6.55009562e-01 9.58087302e-01
-2.11073400e-02 7.42971282e-01 7.42993776e-01 -1.26798593e-01
-1.52277125e-01 -5.51708763e-02 1.08697271e+00 1.08712506e+00
1.07814447e+00 -6.07987009e-01 -1.47523472e-02 5.44400097e-01
-8.50727554e-02 -3.81739687e-01 -2.02824243e+00 -1.54241465e+00
1.25358128e+00 -1.26724172e+00 -3.07549050e-01 2.19465251e-01
6.73867521e-01 5.82179609e-01 -5.72951473e+00 1.98265178e+00
-4.68450752e-01 1.73679092e-01 3.41075173e-01 9.10817772e-01
-2.53882391e+00 -1.23999144e+00 7.78658870e-01 1.59758483e-01
-1.65803177e+00 -1.68492264e-02 -3.01821095e-03 4.67904570e-01
1.40156536e+00 1.40038189e+00 -9.44384094e-02 -1.43798358e+00
8.40076463e-01 1.44156322e+00 3.98628560e-01 -1.25250501e+00
-1.48738248e+00 -2.20453050e+00 1.89798070e-01 2.04232986e-01
-4.59992246e-01 -9.76977222e-02 -4.39379542e-01 -1.19158414e-02
5.18598418e-01 7.44090711e-01 -4.36501252e-01 2.94968153e-01
4.19692742e-01 6.81919080e-01 5.82503443e-01 -1.01450876e+00
5.77737961e-01 5.44407417e-01 1.56871500e-01 -1.09951754e+00
5.37741019e-01 -2.59561092e-01 7.48656570e-01 7.48023694e-01
1.03847326e+00 6.02343504e-01 -5.08830470e-01 -4.51691883e-01
3.41974205e-03 7.76516165e-01 1.50757778e+00 -2.33697039e-01
1.21618004e+00 -1.25864072e-01 3.89457344e-01 6.53713147e-02
-6.15733186e-01 6.39984850e-01 1.63079101e-01 -1.30080705e-01
6.48944243e-01 2.56373594e-02 5.93829870e-01 1.78849539e-01
3.65640065e-02 -1.01607601e-01 2.14714866e-01 2.74791905e-01
2.40533168e-01 -8.40977590e-01 1.99185979e-02 1.38224753e-01
-1.26513966e+00 -2.37869600e-01 8.90763372e-01 1.20439162e+00
-8.16461717e-01 3.60037519e-01 7.52071509e-01 4.76954396e-01
-1.52658376e-01 -6.17212439e-01 -9.42738758e-01 9.98525493e-02
-9.43922780e-02 1.09283778e-01 9.87868553e-01 -7.34390473e-01
-4.75920904e-01 -4.44658341e-01 -3.35873008e-01 -4.51804276e-01
-4.37914243e-01 -6.43369836e-02 -3.84119312e-02 8.19698838e-01
9.68516264e-01 -9.66079769e-01 4.83982449e-01 3.00435289e-01
4.76977271e-01 -1.07636799e+00 9.26830305e-01 -3.27820230e-01
-2.84544998e-02 -1.49046901e+00 -4.53102054e-01 -1.64975504e+00
5.87983237e-01 -1.00022894e-01 7.78841490e-01 -5.16778176e-01
6.91474597e-01 -3.81117257e-01 1.19792575e-01 1.10589792e+00
8.73826078e-01 2.18443499e-01 -5.82863051e-02 3.48727028e-01
-4.35782823e-01 -1.22228029e+00 -3.33354084e-01 9.12167400e-01
6.55312580e-01 -2.93685552e-01 -3.91832015e-02 1.00301510e-01
1.40807469e+00 -5.46642922e-01 -6.34627974e-01 4.67754205e-01
-8.74579584e-01 -4.46983970e-01 7.02807352e-01 -2.45980939e-01
-4.38698400e-01 7.75791483e-01 9.11328648e-01 -1.50643922e+00
9.63013509e-02 -4.61598837e-01 4.61079800e-01 7.48437188e-02]
Unique values in Longitude: [ 2.51194074e-01 -6.45883067e-02 -5.79314444e-01 -1.22699469e+00
1.85888724e-02 -7.75128185e-01 9.63325198e-02 6.47902346e-01
1.82645132e-01 -1.05705264e+00 3.45563995e-01 4.92753807e-02
8.25314726e-01 -2.20499191e-02 1.20329302e-01 1.22806832e-01
-1.12030684e+00 2.22261631e+00 1.87600418e-03 6.92072895e-01
2.45869979e-01 -8.82225085e-01 6.04313646e-02 2.29747233e-02
-1.16056580e+00 -4.03568370e-02 1.35156411e-01 -1.14582165e+00
-1.07246765e+00 1.33256722e-01 -1.02487259e+00 8.10464202e-02
6.86890690e-01 -1.17454905e+00 -1.20774497e+00 -1.00404115e+00
1.42160222e-01 -1.06549172e+00 9.36139413e-02 1.55187808e+00
3.83658646e-01 1.45603194e+00 -3.17762926e-02 9.60053082e-01
4.10763374e-01 1.62567903e+00 1.33149595e-02 7.46648567e-02
1.97523365e-02 -1.16860384e+00 -2.87958594e-03 -1.57362237e+00
-1.28746538e+00 -1.25899561e+00 8.37318134e-02 7.42149496e-02
-1.08713055e+00 -1.06894127e+00 4.44763270e-02 -1.03432565e+00
-1.09227633e+00 -1.59380858e+00 8.65721377e-02 6.76256426e-02
-1.13848875e+00 -1.07253778e+00 -3.87649917e-02 -1.16112620e+00
-1.20768521e+00 2.25370733e-01 2.38637148e-02 -1.23131596e+00
-8.44707691e-01 1.08240810e-01 -1.09456305e+00 1.44985373e+00
-1.11918178e+00 1.11526433e-01 -1.00346216e+00 -1.39199724e-02
2.52400989e-01 -1.26478013e+00 -1.38160548e+00 1.81728412e+00
1.88392388e+00 1.88381131e+00 1.59729928e+00 1.94781842e-01
1.73517223e+00 -9.49785706e-01 1.16873184e-01 2.22775930e-02
1.46310430e-01 -1.19800318e+00 3.95371753e-02 1.92519571e-01
1.36067526e-01 1.53213157e+00 1.49169903e-01 -1.05339681e+00
-9.51683895e-01 1.62296546e+00 -1.27418211e+00 1.84554033e+00
-4.61666836e-03 -1.08242299e+00 1.30377768e-01 -2.76375453e-02
1.88864631e+00 -3.05505081e-02 -3.04672992e-02 1.62418274e+00
-9.92039197e-01 -1.63836166e+00 -5.39609903e-02 -5.38726024e-02
3.63765514e-01 1.76806048e+00 -9.70983331e-01 1.74342499e-01
-2.72399591e-02 1.87823608e+00 9.99567544e-01 9.85112670e-01
4.76677531e-01 8.97977344e-01 1.85156448e+00 -1.15136581e+00
3.64919032e-01 1.23049262e-01 2.55844877e-01 4.42297840e-01
1.72802148e+00 3.26785471e-01 2.17110369e-01 1.49287944e-01
1.04304163e+00 1.62667447e+00 4.83899311e-01 -1.20043843e+00
-1.26914311e+00 -1.16643399e+00 1.81136761e-01 1.19741262e-01
3.96712474e-01 3.96925582e-01 -9.92687446e-01 1.53226580e+00
1.08063662e-01 3.60935083e-01 1.01729135e-01 1.63014742e+00
1.61457837e+00 1.07572009e+00 -9.14439432e-01 7.36025553e-02
-1.06388358e+00 5.97396140e-01 1.81657736e+00 -9.47287513e-01
2.56188083e-01 7.87773107e-02 1.81690787e+00 -1.23518824e+00
1.07589613e-01 1.10526758e-01 1.23040484e-01 1.05228621e+00
1.32897301e-01 1.74453755e-01 -1.00361753e+00 1.60835808e+00
5.78074154e-02 -1.02195112e+00 5.31839293e-01 5.31617526e-01
4.96688930e-01 1.31593102e-01 -1.08978245e+00 1.81247111e+00
1.88227218e+00 -2.30785306e-02 2.95819776e-01 1.89010335e+00
2.32454885e-01 -9.74354978e-01 2.61436872e-01 -1.13515428e+00
-1.48767936e+00 1.94704938e-02 -1.27222723e+00 -1.00174779e+00
2.71576910e-02 -1.06647307e+00 1.23101689e-01 -1.03888672e+00
-9.26190481e-01 -1.10752599e+00 -8.71415243e-01 -1.21905108e+00
1.61718096e+00 -1.18820163e+00 -1.01555911e+00 1.01525467e+00
-1.59736305e+00 1.83565622e-01 1.71898154e-01 -1.20176922e+00
-1.02018732e+00 3.54988208e-01 3.20121200e-02 -9.92008654e-01
-1.55002630e+00 1.62639966e+00 -3.15208627e-02 -1.02794471e+00
-9.29802486e-01 -3.53809942e-02 1.73991277e+00 -1.11885378e+00
-1.03742829e+00 1.82671889e+00 1.77719492e+00 1.73046429e+00
-1.05707094e+00 -9.56541949e-01 3.25727775e-02 4.52383143e-01
-1.26440033e+00 4.25617467e-01 3.20342966e-02 -1.05456274e+00
1.37627860e-01 -1.00744599e+00 -1.00014629e+00 1.51139979e+00
1.81048887e+00 9.75963248e-01 2.02047271e-01 -1.00780055e+00
1.16923022e-01 1.59742271e+00 8.10912649e-02 1.87827940e+00
1.87699925e+00 -2.09184452e-02 -4.13692077e-02 7.39050076e-02
-2.37719294e-02 -1.62077911e+00 1.81734535e+00 -1.05569150e+00
1.72920027e+00 1.23676011e-01 1.30409758e-01 -1.60690428e+00
2.25706700e-02 -9.51904772e-01 4.12873595e-01 -1.06882352e+00
-1.07472490e+00 5.73738262e-01 -1.19034095e+00 -1.11490315e+00
-1.89609773e-02 -1.25963036e+00 1.73041564e+00 1.35776123e-01
-4.84722560e-02 1.50182753e+00 -9.57393267e-01 1.68979893e+00
4.70339059e-01 -1.15491013e+00]
Unique values in p90_1200: [-0.46440209 -0.7740401 -1.00290733 -0.8891155 0.05141904 -1.24058306
0.69883952 -0.76724366 0.50880788 -0.57167349 0.18291459 0.57258939
-1.27805142 0.06479819 0.85372265 0.84543013 -0.6490723 -1.6064613
0.37333094 -0.86672327 0.86078777 -1.31138878 0.50851477 0.29350177
-0.65205834 0.06984209 0.64829062 -0.67736943 -0.62796853 0.6350397
-0.71110738 0.79154102 -1.05950158 -0.77720322 -0.78395081 -0.64705108
0.90857047 -0.5701591 0.74174931 2.67399014 0.11269081 1.16547958
-0.27110351 0.9816032 0.1486576 1.55046465 0.3781489 0.62774864
0.47835518 -0.67160498 -0.48251372 -1.42507741 -1.15260915 -0.9839237
0.80234327 0.75669781 -1.15014888 -0.61459548 0.52570433 -0.65929444
-0.53586547 -1.34364287 0.59903627 0.54558682 -0.56628763 -0.62793189
-0.63342767 -0.67242934 -0.8845479 0.91855446 0.3178908 -1.07634125
-1.27633429 0.6296172 -0.5388454 1.82399542 -0.90241527 0.81421414
-0.72904803 0.22968973 -0.7390137 -1.05742418 -1.35069394 -0.37392333
-0.711889 -0.71471627 2.08183271 0.18324434 0.98315423 -0.97212611
0.8582475 0.45727584 0.91785222 -0.94753557 0.40770395 0.74049749
0.76753059 2.15249615 0.94064136 -0.60117969 -0.84536914 2.92471955
-1.0439864 -0.51709435 -0.12620437 -0.8587605 0.87094884 -0.1821941
-0.79025874 0.06911543 0.0693719 2.35121723 -0.6836224 -1.32415607
-0.4859272 -0.48562799 -0.01430431 0.16600592 -0.76295085 1.02837223
-0.53078493 -0.69213475 0.90401508 2.41533459 -0.61427184 0.60393362
-0.39919168 -0.69796637 0.36771915 0.84754295 -1.53399388 -1.44546368
1.46750289 0.24056526 0.85630566 0.73031199 -0.24171944 1.51197591
-0.22698465 -0.97850121 -0.99092165 -0.69648862 0.31593674 0.84623007
-0.71653598 -0.71450865 -0.68703589 2.15483491 0.62829211 -0.73497125
0.88767432 1.40020408 0.86992297 0.56721574 -0.9887783 0.73751756
-0.5535985 -0.54273519 -0.37507134 -0.85516383 0.87461269 0.61212843
-0.37357526 -1.08455193 0.88601948 0.79191351 0.847488 3.39251372
0.8855676 1.02840887 -0.72869996 2.4291473 0.60823864 -0.6007156
-0.42425241 -0.4234891 -0.4473713 0.88510962 -0.57680898 -0.37157236
-0.74491249 0.06275255 -0.84673697 -0.73718788 -0.03588438 -0.73810384
0.8074238 -0.56798521 -1.28354291 0.36280959 -1.13872683 -0.66234154
0.39103955 -0.56876683 0.8495825 -0.64845556 -0.93073072 -0.5016329
-0.69034557 -1.13338677 -1.03037337 3.32806661 -0.80016945 -0.69179889
3.16020736 -1.31297401 0.78458581 0.26632822 -1.0344262 -0.77791156
0.39768333 0.46518364 -0.68366515 -1.32773504 2.80546126 -0.05791022
-0.61694035 -0.93657456 -0.25327277 0.60168645 -0.52231533 -0.57502591
-0.31515519 0.11951778 1.41507931 -0.57164906 -0.83406005 0.30977537
-0.23249264 -0.92990635 0.19970723 0.78081205 0.46526913 -1.21544844
0.6839643 -0.63543668 -0.68036158 1.90550386 -0.36249212 1.86577552
0.99139789 -0.64626335 0.72317359 3.44041245 0.63914931 -0.69222634
-0.68616267 -0.30841981 -0.17197196 0.74752598 -0.43544547 -1.43403064
-0.37447901 -1.23962313 1.50649846 0.64397338 0.87075955 -1.32239681
0.01604457 -0.87118706 -0.7420669 -0.61297728 -0.65685188 -0.45919332
-1.01355569 -0.51319845 0.15930108 -0.94522124 1.41655707 0.7829554
-0.2453955 1.79283439 -0.85491957 2.35702443 0.06105496 -0.61618926]
Unique values in p00_1200: [-5.08015517e-01 -7.31805479e-01 -9.16579967e-01 -8.13687716e-01
2.97992988e-02 -1.16297618e+00 5.78638089e-01 -7.94808204e-01
3.91083025e-01 -5.33384862e-01 8.97920089e-02 4.69818677e-01
-1.23635936e+00 6.84452123e-03 7.15667514e-01 7.07943084e-01
-6.21822486e-01 -1.53698152e+00 3.13052077e-01 -8.08000919e-01
6.93772524e-01 -1.22738722e+00 4.10202902e-01 2.15109143e-01
-6.05215507e-01 1.77428509e-02 5.26550083e-01 -6.04756630e-01
-5.94857997e-01 5.14919735e-01 -6.55500783e-01 6.84278139e-01
-9.27685884e-01 -7.29762384e-01 -7.15717468e-01 -6.03494718e-01
7.81478129e-01 -5.18684408e-01 6.16451743e-01 2.71049887e+00
3.03728951e-02 1.29619613e+00 -2.99816449e-01 1.44487229e+00
1.10945967e-02 1.70117151e+00 2.93577117e-01 5.15482405e-01
3.94213222e-01 -6.18304428e-01 -4.57473489e-01 -1.33566964e+00
-1.07854608e+00 -9.19213047e-01 6.94264178e-01 6.57062361e-01
-1.06389698e+00 -5.59966953e-01 4.26514888e-01 -6.27219754e-01
-5.00252847e-01 -1.24745271e+00 4.91019889e-01 4.42919742e-01
-5.29183952e-01 -5.94819757e-01 -6.34037355e-01 -6.25848585e-01
-8.26552662e-01 7.41047784e-01 2.37097001e-01 -1.02156557e+00
-1.19926898e+00 5.15580736e-01 -5.03530540e-01 1.87360548e+00
-8.21532329e-01 6.80885727e-01 -6.96395467e-01 1.56219923e-01
-7.63282259e-01 -9.95605695e-01 -1.26138673e+00 -3.73608247e-01
-7.16569669e-01 -7.19355708e-01 2.22731228e+00 1.18559229e-01
9.67339719e-01 -9.38529585e-01 7.22015313e-01 3.95770126e-01
7.71098768e-01 -8.62492567e-01 3.18859057e-01 5.95184977e-01
6.34823213e-01 2.29751500e+00 7.88295731e-01 -5.48025225e-01
-8.10317155e-01 2.94563512e+00 -9.78550218e-01 -5.15805501e-01
-1.68910848e-01 -7.93278614e-01 7.30728514e-01 -2.17267747e-01
-7.80506536e-01 1.30612125e-02 1.32906511e-02 2.36799087e+00
-6.41657992e-01 -1.23347007e+00 -4.96958766e-01 -4.96685624e-01
-1.45229515e-01 1.62239953e-01 -7.25807301e-01 8.59066589e-01
-5.06458613e-01 -6.98154496e-01 1.12211785e+00 2.91903117e+00
-6.77073466e-01 1.02303319e+00 -3.99911735e-01 -6.63869826e-01
2.14371662e-01 7.10253857e-01 -1.42517087e+00 -1.39896189e+00
1.43698944e+00 1.42338893e-01 7.03228668e-01 5.98839605e-01
-1.07847425e-01 1.66393145e+00 -3.41224639e-01 -9.31274958e-01
-8.70566618e-01 -6.46339630e-01 2.39833875e-01 7.08680565e-01
-7.63260407e-01 -7.61539619e-01 -6.47443120e-01 2.29979300e+00
5.14428081e-01 -7.76742652e-01 7.63784049e-01 1.55343495e+00
1.05531847e+00 7.66444443e-01 -9.52416079e-01 6.41657203e-01
-5.03426747e-01 -4.51065599e-01 -3.74722663e-01 -8.19516547e-01
7.14503933e-01 5.02016549e-01 -3.73258626e-01 -1.02905510e+00
7.57212274e-01 6.61061146e-01 7.10204692e-01 3.96361012e+00
7.43358558e-01 8.59061126e-01 -6.96045847e-01 2.53884062e+00
4.99978917e-01 -5.56541764e-01 -5.05715669e-01 -5.05081982e-01
-5.28741463e-01 7.43216525e-01 -5.22847079e-01 -3.71128126e-01
-7.36656465e-01 5.41326189e-03 -8.66633386e-01 -7.38371791e-01
-1.13173676e-01 -6.95259200e-01 6.64409856e-01 -5.31735090e-01
-1.18653187e+00 2.78931292e-01 -1.07826201e+00 -6.21664064e-01
3.05027192e-01 -5.33057093e-01 7.12198622e-01 -6.15474687e-01
-8.93488619e-01 -4.64820984e-01 -6.55915957e-01 -1.09147931e+00
-9.78867062e-01 3.41427422e+00 -7.47980895e-01 -6.58423392e-01
3.68922351e+00 -1.21405629e+00 6.39160693e-01 1.74148905e-01
-9.43511679e-01 -7.48226722e-01 2.39265742e-01 3.71793801e-01
-6.41690769e-01 -1.23407207e+00 2.89648064e+00 -7.50213277e-02
-5.77835844e-01 -9.00715932e-01 -2.82586709e-01 6.00008649e-01
-4.61046174e-01 -5.24398520e-01 -3.16849528e-01 1.08436620e-01
1.38337731e+00 -5.33363011e-01 -7.98593940e-01 2.30361342e-01
-3.38963031e-01 -8.43339914e-01 8.48372295e-02 6.76531858e-01
3.71875743e-01 -1.12569679e+00 5.58862674e-01 -5.87887436e-01
-6.42007613e-01 2.03079818e+00 -3.62169098e-01 2.28888374e+00
8.14511813e-01 -6.06908982e-01 5.97725189e-01 3.45685145e+00
5.25555849e-01 -6.98247364e-01 -6.78133254e-01 -3.36024032e-01
-2.07265320e-01 6.50069949e-01 -4.19495951e-01 -1.34708420e+00
-3.74159992e-01 -1.14549351e+00 1.47197882e+00 5.25462981e-01
7.30559166e-01 -1.22421987e+00 -2.22376312e-03 -8.36391204e-01
-7.85614275e-01 -5.58470140e-01 -5.99588801e-01 -5.06158158e-01
-9.19344155e-01 -4.54496251e-01 9.20863941e-02 -8.73795146e-01
1.38488505e+00 6.49332468e-01 -2.74556360e-01 1.89964129e+00
-8.20254028e-01 2.34002122e+00 -3.73934105e-02 -5.77300487e-01]
Unique values in p10_1200: [-0.55484798 -0.67951526 -0.85797515 -0.76463416 0.05124564 -1.11664732
0.51146131 -0.84850242 0.30479419 -0.48019628 0.01334469 0.42912495
-1.23111107 -0.0179615 0.63616877 0.62671111 -0.56991594 -1.49883829
0.30649687 -0.78248467 0.56645936 -1.17270967 0.3569444 0.17895664
-0.55330602 0.00496691 0.4466741 -0.55270331 -0.54257261 0.43652834
-0.60408003 0.6406992 -0.82873326 -0.67968603 -0.66533631 -0.55133212
0.70820366 -0.46522375 0.54923166 2.66640055 -0.04251726 1.32803925
-0.31753264 1.7730162 -0.11300517 1.70267394 0.26779231 0.45630253
0.37236395 -0.56660099 -0.41019557 -1.29437692 -1.03291868 -0.8717774
0.64900165 0.62412947 -1.02310994 -0.50709761 0.38718078 -0.57537556
-0.4465646 -1.2046668 0.42785924 0.38687942 -0.47592703 -0.54253243
-0.63164435 -0.5742756 -0.77777844 0.61325542 0.20095586 -0.97548514
-1.15459396 0.44358517 -0.44988457 1.88571449 -0.77552327 0.60657027
-0.6455571 0.13171356 -0.7902296 -0.94929201 -1.21886484 -0.40629799
-0.73780315 -0.74051538 2.21440194 0.07830769 0.91335895 -0.89127032
0.64559126 0.3902245 0.67687737 -0.81408218 0.27513543 0.49449479
0.54882985 2.31092227 0.69287452 -0.49495284 -0.7611836 2.88741739
-0.93200906 -0.54479765 -0.19484428 -0.74696949 0.64538031 -0.23833042
-0.7954833 -0.00889059 -0.00867964 2.32251455 -0.58997139 -1.19051498
-0.50275302 -0.50250189 -0.25352896 0.12155776 -0.67532134 0.74853556
-0.45897557 -0.72021884 1.34042512 3.31275073 -0.74154502 1.3229714
-0.43219479 -0.61259845 0.08246143 0.6286599 -1.38302875 -1.37299249
1.37373535 0.06308905 0.59178358 0.51151153 0.02335986 1.66704826
-0.4480513 -0.8841281 -0.80711576 -0.59503423 0.19626973 0.62938316
-0.80745228 -0.80596557 -0.5958479 2.31312219 0.44255553 -0.81526251
0.70215638 1.56022144 1.08171829 0.959487 -0.90531366 0.6125623
-0.44976905 -0.3717572 -0.4073879 -0.77087732 0.58743898 0.44151584
-0.40595645 -0.98306935 0.69039835 0.58605775 0.6286147 4.47142159
0.65671142 0.74848032 -0.64520551 2.50869426 0.45155612 -0.50369728
-0.59657618 -0.59596844 -0.61588326 0.65718355 -0.46948799 -0.40383689
-0.75285102 -0.01901124 -0.89047172 -0.75783349 -0.18703406 -0.64465804
0.54449028 -0.47850365 -1.14263252 0.24604924 -1.03308995 -0.56972508
0.26944978 -0.47983465 0.63061371 -0.56345681 -0.84591074 -0.41065263
-0.60451197 -1.04642811 -0.9322401 3.35431821 -0.69815432 -0.60705846
4.16956013 -1.17081362 0.53892518 0.10300408 -0.89642356 -0.69812419
0.10125619 0.33710995 -0.59000655 -1.19096852 2.84675399 -0.04930286
-0.52528464 -0.85290729 -0.30087752 0.55519355 -0.40665459 -0.47093953
-0.35068215 0.06728297 1.32068609 -0.48017619 -0.74938036 0.19034802
-0.44305879 -0.79193228 -0.02220565 0.63922756 0.33718026 -1.08573389
0.47644337 -0.53548565 -0.59035312 2.05107028 -0.39501208 2.62165876
0.69035817 -0.55474753 0.51987928 3.39411772 0.46414791 -0.72030925
-0.6942467 -0.35322361 -0.22541717 0.61943329 -0.37497672 -1.3059702
-0.40684043 -1.10289178 1.40765835 0.44915027 0.6451995 -1.18111257
0.02109465 -0.787658 -0.82852231 -0.50558077 -0.54921758 -0.56120164
-0.8734399 -0.40004478 0.06768478 -0.8256594 1.32217782 0.56272251
-0.28938569 1.91377103 -0.77126406 2.27052005 -0.13138306 -0.52473717]
Unique values in p90u_1200: [-5.93106582e-01 -9.64721121e-01 -1.18332857e+00 -9.08713196e-01
1.76309166e-01 -1.47426642e+00 9.96001468e-01 -9.08642492e-01
7.05455799e-01 -3.89150151e-01 -2.90171376e-02 9.20271789e-01
-1.55821312e+00 3.29105256e-01 1.14480946e+00 1.14158363e+00
-4.96839854e-01 -1.93156417e+00 6.77749011e-01 -1.15469932e+00
9.12936339e-01 -1.60116086e+00 8.24358576e-01 5.91413862e-01
-5.59964491e-01 3.45543733e-01 8.84666135e-01 -5.76668105e-01
-4.68945260e-01 8.69343441e-01 -5.77341994e-01 1.12399623e+00
-1.32912173e+00 -7.58739708e-01 -7.56364525e-01 -4.84069101e-01
1.13434760e+00 -3.67298465e-01 1.05935810e+00 2.41397480e+00
-1.55796685e-01 1.41521018e-01 -1.05221853e-01 -4.83870248e-01
-8.27018835e-03 1.41540359e+00 7.05466846e-01 9.44973694e-01
8.27208796e-01 -5.97912185e-01 -5.89383620e-01 -1.63473711e+00
-1.31039755e+00 -1.04352749e+00 1.13517616e+00 1.09370435e+00
-1.33142290e+00 -4.36322395e-01 8.60428219e-01 -5.04042735e-01
-3.44574038e-01 -1.48128591e+00 8.91526548e-01 8.56904110e-01
-4.03721624e-01 -4.68912118e-01 -5.28700451e-01 -5.94045608e-01
-9.04216918e-01 1.02038300e+00 6.17319930e-01 -1.15933259e+00
-1.51293108e+00 8.83373594e-01 -3.48153384e-01 5.88121748e-01
-9.40359474e-01 1.12628303e+00 -6.03701004e-01 5.45235882e-01
-9.33061585e-01 -1.15086036e+00 -1.56637050e+00 -2.95081848e-01
-6.82601276e-01 -6.84777607e-01 1.84326799e+00 8.81291084e-02
1.23967317e+00 -9.47910347e-01 1.15801106e+00 7.59245414e-01
1.18264668e+00 -9.80113413e-01 7.15641469e-01 9.59081178e-01
1.01253937e+00 1.54743063e+00 1.19273292e+00 -4.04947881e-01
-7.76459679e-01 2.83802787e+00 -1.12989468e+00 -4.07521917e-01
5.74947685e-02 -8.64130454e-01 1.16458424e+00 3.04231221e-03
-8.45833810e-01 3.54679903e-01 3.54867708e-01 2.21394019e+00
-5.34511364e-01 -1.44732742e+00 -3.67232181e-01 -3.66989139e-01
-1.62226251e-01 3.58723238e-01 -6.47327044e-01 1.26218770e+00
-6.48442827e-01 -6.47514849e-01 -4.17254645e-01 3.28000519e-01
-7.74029259e-01 -4.92829661e-01 -3.19551759e-01 -5.94001418e-01
2.11892725e-01 1.14200343e+00 -1.84321324e+00 -1.73223893e+00
1.77358122e+00 5.21147023e-02 9.49160645e-01 9.65223512e-01
-1.13870053e+00 1.38511172e+00 -3.86211552e-01 -1.04684722e+00
-1.26388263e+00 -6.36887285e-01 3.17063629e-01 1.13611518e+00
-9.00829797e-01 -8.99125188e-01 -5.39957715e-01 1.55039133e+00
8.82036863e-01 -8.97416161e-01 1.23333198e+00 1.29962722e+00
7.25385243e-01 -6.60340838e-01 -9.67204568e-01 1.07842585e+00
-3.43049502e-01 -8.13766627e-01 -2.96286011e-01 -7.90942773e-01
9.27308959e-01 9.23851135e-01 -2.94706238e-01 -1.17012144e+00
1.21765578e+00 1.09569288e+00 1.14197029e+00 4.78178383e-01
1.16634077e+00 1.26190047e+00 -6.03237015e-01 2.28399152e+00
9.55711732e-01 -4.17099982e-01 -6.01381058e-01 -6.01149063e-01
-6.06694840e-01 1.17400764e+00 -3.87283147e-01 -2.93402649e-01
-8.10364039e-01 3.27558625e-01 -1.00566265e+00 -7.14495016e-01
-9.21970113e-02 -6.11146927e-01 8.27462885e-01 -4.04472845e-01
-1.40723101e+00 6.93336841e-01 -1.25938746e+00 -5.06915049e-01
7.17486378e-01 -3.84587590e-01 1.14588105e+00 -4.89404978e-01
-8.95319372e-01 -2.98517578e-01 -5.81661513e-01 -1.18431841e+00
-1.10158691e+00 3.43445294e+00 -7.85827844e-01 -5.51612683e-01
4.36883337e-01 -1.43233394e+00 9.82468447e-01 4.67230446e-01
-1.12168869e+00 -6.66030231e-01 2.60379605e-01 7.99811334e-01
-5.34544506e-01 -1.46612561e+00 2.94455759e+00 7.64078554e-02
-4.48408211e-01 -9.05163678e-01 -8.61982928e-02 8.34201777e-01
-3.06747864e-01 -3.66039066e-01 -2.46153074e-01 2.99376800e-01
1.69879057e+00 -3.89128056e-01 -7.63169701e-01 5.96816023e-01
-4.04682745e-01 -1.07318635e+00 -3.19778311e-02 1.12694587e+00
7.99877618e-01 -1.43364526e+00 9.26933349e-01 -4.61963326e-01
-5.32975781e-01 1.08401582e+00 -2.83979247e-01 1.02733723e-01
1.14959297e+00 -4.82411996e-01 9.85362856e-01 3.32128375e+00
9.46155762e-01 -6.47779986e-01 -7.66815331e-01 -1.59585931e-01
1.91383213e-02 1.08791553e+00 -5.14327831e-01 -1.64718970e+00
-2.95645264e-01 -1.48979569e+00 1.76662138e+00 8.91990537e-01
1.16426387e+00 -1.44591667e+00 1.22972494e-01 -8.13567775e-01
-9.10895050e-01 -4.33969306e-01 -5.20923107e-01 -6.59070391e-01
-1.10477408e+00 -2.94330627e-01 4.60933448e-01 -9.83681711e-01
1.70146403e+00 1.02723237e+00 -6.81137582e-02 8.39405086e-01
-7.89760706e-01 2.53800356e+00 -1.41744438e-01 -4.79517587e-01]
Unique values in p00u_1200: [-6.60152234e-01 -9.53321916e-01 -1.12000468e+00 -8.41270259e-01
1.48003467e-01 -1.43765186e+00 8.91488928e-01 -9.72020972e-01
5.95329216e-01 -3.59929308e-01 -1.04319025e-01 8.26456825e-01
-1.55891554e+00 2.60987699e-01 1.02811838e+00 1.02586448e+00
-4.89610972e-01 -1.92443294e+00 6.21962395e-01 -1.12816005e+00
7.77201986e-01 -1.56488526e+00 7.31028159e-01 5.09950026e-01
-5.22933463e-01 2.86049355e-01 7.77532833e-01 -4.97158418e-01
-4.51325777e-01 7.63296075e-01 -5.29478029e-01 1.03764057e+00
-1.22392990e+00 -7.28927043e-01 -6.92854387e-01 -4.51646285e-01
1.03529362e+00 -3.14861750e-01 9.50214261e-01 2.59268325e+00
-2.18574950e-01 3.25657938e-01 -1.53604881e-01 -1.76712472e-01
-1.47298111e-01 1.67664043e+00 6.21983073e-01 8.43753917e-01
7.47591184e-01 -5.51830876e-01 -5.86290653e-01 -1.57929158e+00
-1.26106024e+00 -9.99057371e-01 1.04828970e+00 1.01272366e+00
-1.26796563e+00 -3.81920291e-01 7.68372508e-01 -4.90107242e-01
-3.17777339e-01 -1.40811033e+00 7.94312976e-01 7.61207604e-01
-3.76481994e-01 -4.51284421e-01 -5.62345605e-01 -5.58954424e-01
-8.63137174e-01 8.73860989e-01 5.34505073e-01 -1.13615724e+00
-1.47938717e+00 7.83839603e-01 -3.21902587e-01 7.56265577e-01
-8.66362932e-01 1.01202061e+00 -5.93734709e-01 4.66288568e-01
-9.92775415e-01 -1.11633124e+00 -1.50601415e+00 -3.09278708e-01
-7.27055690e-01 -7.29268229e-01 2.12088516e+00 3.41197442e-02
1.27724613e+00 -9.52719154e-01 1.04350276e+00 7.05263453e-01
1.06281595e+00 -9.01419268e-01 6.28114081e-01 8.31584953e-01
9.01331624e-01 1.82283342e+00 1.06793374e+00 -3.52092371e-01
-7.71844095e-01 3.00451532e+00 -1.08861867e+00 -4.25840223e-01
-9.19015166e-04 -8.10666916e-01 1.04791750e+00 -4.88297886e-02
-8.74024107e-01 2.89140706e-01 2.89316469e-01 2.35133040e+00
-5.07125182e-01 -1.38099742e+00 -4.05151950e-01 -4.04914154e-01
-3.07283287e-01 3.70001768e-01 -6.33229563e-01 1.12426043e+00
-6.46577170e-01 -6.92058286e-01 -2.32997809e-01 7.29074094e-01
-8.69898859e-01 -1.57998942e-01 -3.35581040e-01 -5.79497952e-01
6.97891806e-02 1.02642279e+00 -1.80649968e+00 -1.74589473e+00
1.81907004e+00 -2.67250770e-02 8.29062245e-01 8.53648308e-01
-1.05791297e+00 1.64677115e+00 -5.19831773e-01 -1.03056847e+00
-1.17270549e+00 -5.97270636e-01 2.51723984e-01 1.01946466e+00
-9.86403509e-01 -9.84919867e-01 -5.16802455e-01 1.82589375e+00
7.82619604e-01 -9.80252858e-01 1.13373093e+00 1.55917942e+00
9.87331153e-01 -5.04457729e-01 -9.69165349e-01 1.00026520e+00
-2.91671447e-01 -7.36329743e-01 -3.10519384e-01 -7.86029158e-01
8.03431945e-01 8.23530897e-01 -3.08896166e-01 -1.14633699e+00
1.11287723e+00 9.84498276e-01 1.02640211e+00 9.16560923e-01
1.04802089e+00 1.12395026e+00 -5.93259117e-01 2.54276671e+00
8.57639150e-01 -3.80090294e-01 -7.04837249e-01 -7.04682165e-01
-7.16003334e-01 1.05595088e+00 -3.31600538e-01 -3.07376338e-01
-8.38427043e-01 2.60263971e-01 -1.07093594e+00 -7.55663612e-01
-1.75451118e-01 -5.86187263e-01 7.23873594e-01 -3.78642838e-01
-1.32633737e+00 6.09266144e-01 -1.23223416e+00 -4.80068105e-01
6.32756277e-01 -3.59422698e-01 1.03042397e+00 -4.73172014e-01
-8.92598061e-01 -2.67457586e-01 -5.66026277e-01 -1.18754294e+00
-1.08057909e+00 3.72536879e+00 -7.49222435e-01 -5.37904287e-01
8.59810333e-01 -1.35187152e+00 8.60730501e-01 3.71356172e-01
-1.04188241e+00 -6.62716298e-01 1.10338610e-01 7.10484631e-01
-5.07156199e-01 -1.39542856e+00 3.21292822e+00 4.96592118e-02
-4.20805146e-01 -9.04948991e-01 -1.34446775e-01 8.69797775e-01
-2.34279841e-01 -3.15564800e-01 -2.59506921e-01 2.99924249e-01
1.73951169e+00 -3.59908630e-01 -7.57431575e-01 5.15450356e-01
-5.27679049e-01 -9.98813371e-01 -1.31520847e-01 1.04272734e+00
7.10557004e-01 -1.37097690e+00 8.18464803e-01 -4.21932093e-01
-5.11022973e-01 1.32691453e+00 -2.97647370e-01 4.54398756e-01
1.00494875e+00 -4.56464243e-01 8.78523863e-01 3.52063656e+00
8.44250187e-01 -6.92337438e-01 -7.91653556e-01 -2.08463440e-01
-3.23804920e-02 1.00865010e+00 -5.18074148e-01 -1.59699396e+00
-3.09868029e-01 -1.42797562e+00 1.81046802e+00 7.88088918e-01
1.04761767e+00 -1.36717940e+00 9.70426979e-02 -8.10935729e-01
-9.94730513e-01 -3.79645718e-01 -4.65293721e-01 -7.25949420e-01
-1.01781226e+00 -2.25491719e-01 3.85768692e-01 -9.25235078e-01
1.74232388e+00 9.15940585e-01 -1.16074430e-01 1.05189800e+00
-7.86266954e-01 2.63471115e+00 -2.34248824e-01 -4.52401029e-01]
Unique values in p10u_1200: [-7.34917416e-01 -9.19337092e-01 -1.07985274e+00 -8.01030316e-01
1.79466807e-01 -1.42813120e+00 8.43131026e-01 -1.07547678e+00
5.16117799e-01 -2.94006913e-01 -1.76696467e-01 8.04402400e-01
-1.60449737e+00 2.34136711e-01 9.74370361e-01 9.69694516e-01
-4.30533702e-01 -1.94218850e+00 6.31583555e-01 -1.13707266e+00
6.68871941e-01 -1.55169978e+00 6.89321366e-01 4.80072359e-01
-4.65987263e-01 2.75716221e-01 7.11428052e-01 -4.38741093e-01
-3.90266191e-01 6.98485628e-01 -4.72705091e-01 1.02144448e+00
-1.13731138e+00 -6.82980021e-01 -6.44833410e-01 -3.90680506e-01
9.91781472e-01 -2.46518476e-01 9.03334999e-01 2.65317636e+00
-2.88946346e-01 3.71975499e-01 -1.86768277e-01 3.95367133e-02
-2.87081927e-01 1.75127092e+00 6.08362164e-01 8.00752479e-01
7.42462248e-01 -4.96459174e-01 -5.45989593e-01 -1.57880193e+00
-1.24251198e+00 -9.67296073e-01 1.03047064e+00 1.00614441e+00
-1.25471850e+00 -3.17139523e-01 7.45628801e-01 -4.31105852e-01
-2.49556789e-01 -1.39816535e+00 7.45382185e-01 7.17988045e-01
-3.11339107e-01 -3.90226732e-01 -5.85329827e-01 -5.03985904e-01
-8.24153061e-01 7.67074556e-01 5.05375193e-01 -1.11150841e+00
-1.47339121e+00 7.25169512e-01 -2.53897236e-01 8.05102791e-01
-8.29933748e-01 9.62739936e-01 -5.40268095e-01 4.48071427e-01
-1.05510430e+00 -1.09083013e+00 -1.50122729e+00 -3.72825486e-01
-7.91195258e-01 -7.93444398e-01 2.19407544e+00 3.75761910e-03
1.24695044e+00 -9.18488732e-01 9.93764267e-01 7.19270450e-01
9.96713799e-01 -8.64321926e-01 5.93683561e-01 7.46200951e-01
8.34331756e-01 1.91363324e+00 1.00108384e+00 -2.85681146e-01
-7.27962836e-01 3.05912654e+00 -1.06167811e+00 -4.90717946e-01
-3.82164768e-02 -7.71436359e-01 9.88743159e-01 -8.20155334e-02
-9.33315305e-01 2.67074785e-01 2.67242484e-01 2.39648824e+00
-4.48980602e-01 -1.36968708e+00 -4.32210693e-01 -4.31983806e-01
-4.37695440e-01 3.21182403e-01 -5.81758823e-01 1.04383724e+00
-6.07979069e-01 -7.56382899e-01 -6.74651711e-02 1.03620200e+00
-9.76282771e-01 7.23268178e-02 -3.99696799e-01 -5.25204771e-01
-6.95564774e-02 9.70118696e-01 -1.81546579e+00 -1.77347394e+00
1.79842396e+00 -9.93181336e-02 7.41554700e-01 7.83666901e-01
-9.84015672e-01 1.72237736e+00 -6.59946058e-01 -1.00065931e+00
-1.13874472e+00 -5.44283009e-01 2.19980935e-01 9.65511903e-01
-1.07137605e+00 -1.07005912e+00 -4.59180653e-01 1.91674060e+00
7.24044942e-01 -1.06084750e+00 1.10296597e+00 1.63565720e+00
1.05664156e+00 -3.69017730e-01 -9.35742009e-01 9.97414189e-01
-2.22133056e-01 -6.74239939e-01 -3.74088161e-01 -7.43499663e-01
6.97331463e-01 7.78438635e-01 -3.72430899e-01 -1.12220860e+00
1.07658789e+00 9.31656416e-01 9.70089102e-01 1.26052420e+00
9.88802347e-01 1.04347225e+00 -5.39764998e-01 2.61360924e+00
8.27446228e-01 -3.15304698e-01 -8.34303789e-01 -8.34136090e-01
-8.41465526e-01 9.97177437e-01 -2.64205798e-01 -3.70872284e-01
-8.97407970e-01 2.33919688e-01 -1.13869638e+00 -8.18727503e-01
-2.63179874e-01 -5.32751230e-01 6.24333036e-01 -3.13617842e-01
-1.31164248e+00 5.87291266e-01 -1.21282431e+00 -4.20540809e-01
6.09102012e-01 -2.93424899e-01 9.74271714e-01 -4.13260696e-01
-8.55719949e-01 -1.96613200e-01 -5.10999671e-01 -1.16577682e+00
-1.05308501e+00 3.80341456e+00 -7.04327129e-01 -4.81504361e-01
1.19435211e+00 -1.33898532e+00 7.79750634e-01 2.96560231e-01
-1.01246730e+00 -6.12891666e-01 -3.59673360e-02 6.90090809e-01
-4.49010196e-01 -1.38458271e+00 3.28156458e+00 8.25268684e-02
-3.58137018e-01 -8.68159276e-01 -1.67591393e-01 8.35347815e-01
-1.61445714e-01 -2.47120220e-01 -3.22190225e-01 2.47848578e-01
1.71688275e+00 -2.93987184e-01 -7.12929106e-01 4.81246253e-01
-6.63053423e-01 -9.63364022e-01 -2.45719440e-01 1.03314396e+00
6.90159861e-01 -1.36422404e+00 7.51005037e-01 -3.59389829e-01
-4.53113891e-01 1.40783305e+00 -3.60948444e-01 7.19211262e-01
9.05120501e-01 -3.95662156e-01 8.17907109e-01 3.59187695e+00
7.99401022e-01 -7.56659110e-01 -8.48222813e-01 -2.42700856e-01
-6.15562443e-02 1.00445755e+00 -4.78742258e-01 -1.59746881e+00
-3.73427229e-01 -1.42232684e+00 1.78949645e+00 7.25613422e-01
9.88427491e-01 -1.35509430e+00 1.29541802e-01 -7.69167489e-01
-1.08024042e+00 -3.14742412e-01 -4.05980582e-01 -8.18263864e-01
-9.87612324e-01 -1.52241994e-01 3.64764438e-01 -8.89496519e-01
1.71975336e+00 8.49237245e-01 -1.43738663e-01 1.11016717e+00
-7.43154401e-01 2.64459411e+00 -3.40844283e-01 -3.91292115e-01]
Unique values in p90r_1200: [-2.52291243e-01 -4.44835359e-01 -6.44419989e-01 -7.14628835e-01
-8.50404057e-02 -7.86412518e-01 2.73973898e-01 -4.89553507e-01
2.19599157e-01 -6.58732279e-01 3.67550345e-01 1.18071814e-01
-7.69910574e-01 -2.16348637e-01 4.08150904e-01 3.96114006e-01
-6.91751961e-01 -9.95369865e-01 -2.38741515e-03 -4.22071295e-01
6.57981405e-01 -7.87642155e-01 9.76406742e-02 -6.17089038e-02
-6.32805003e-01 -2.23825727e-01 2.94279818e-01 -6.62514820e-01
-6.81252672e-01 2.85446743e-01 -7.24148928e-01 3.14529332e-01
-6.00096679e-01 -6.61024591e-01 -6.75920112e-01 -7.01056584e-01
5.20171895e-01 -6.78254164e-01 2.88549036e-01 2.47490999e+00
3.67268319e-01 2.00860710e+00 -3.93397080e-01 2.30753281e+00
2.83077719e-01 1.41900216e+00 -2.17931059e-02 1.94746967e-01
3.90140992e-02 -6.30168618e-01 -2.89550350e-01 -9.63385379e-01
-7.91225021e-01 -7.52105667e-01 3.23069100e-01 2.81092251e-01
-7.65209754e-01 -6.89868022e-01 9.25675786e-02 -7.03284595e-01
-6.38100336e-01 -9.69639828e-01 1.96269911e-01 1.32881598e-01
-6.33910548e-01 -6.81215444e-01 -6.30325425e-01 -6.35639935e-01
-7.10777479e-01 6.54980641e-01 -4.30996564e-02 -8.04587445e-01
-8.12977174e-01 2.61102201e-01 -6.39960584e-01 2.76910893e+00
-7.06880999e-01 3.54069471e-01 -7.30386229e-01 -1.32447960e-01
-4.12464339e-01 -7.78291279e-01 -8.95781218e-01 -3.89470141e-01
-6.18109158e-01 -6.21118946e-01 1.96375358e+00 2.48535093e-01
5.50393873e-01 -8.27952790e-01 4.03029300e-01 6.94650823e-02
4.87975731e-01 -7.49643010e-01 2.24162660e-02 3.88634659e-01
3.83998140e-01 2.39638249e+00 5.19777058e-01 -6.97110467e-01
-7.68859179e-01 2.50508684e+00 -7.74875372e-01 -5.39148460e-01
-2.91870865e-01 -7.04072013e-01 4.19781684e-01 -3.39701459e-01
-5.96203583e-01 -2.34501001e-01 -2.34218974e-01 2.08290421e+00
-7.17119695e-01 -9.68315882e-01 -5.22713074e-01 -5.22397205e-01
1.39232839e-01 -5.96298032e-02 -7.48465267e-01 6.10939357e-01
-3.18418599e-01 -6.17445831e-01 2.09618202e+00 4.12716885e+00
-3.44404536e-01 1.61897034e+00 -4.11155735e-01 -6.82860224e-01
4.62954326e-01 3.99599856e-01 -9.51713198e-01 -9.01483572e-01
8.99982845e-01 3.91195461e-01 6.12710485e-01 3.63545567e-01
7.16236833e-01 1.37884156e+00 -2.49529327e-02 -7.38699247e-01
-5.40019359e-01 -6.36341618e-01 2.59895127e-01 4.03187235e-01
-4.03853501e-01 -4.01842086e-01 -7.17852964e-01 2.39766853e+00
2.60007938e-01 -4.41390122e-01 3.80489729e-01 1.25963453e+00
8.66376548e-01 1.72218082e+00 -8.39010491e-01 2.61260136e-01
-6.72419597e-01 -1.71675613e-01 -3.90357961e-01 -7.72169044e-01
6.68845072e-01 1.87459398e-01 -3.89206164e-01 -8.08738877e-01
3.93429112e-01 3.44119570e-01 3.99532169e-01 5.77907799e+00
4.44994868e-01 6.11300351e-01 -7.30209117e-01 2.15532865e+00
1.47727482e-01 -6.83849573e-01 -1.69672095e-01 -1.68490968e-01
-2.06944739e-01 4.36319727e-01 -6.70125028e-01 -3.86836012e-01
-5.48649375e-01 -2.18558597e-01 -5.37336721e-01 -6.32279306e-01
2.78526120e-02 -7.39508100e-01 6.46689057e-01 -6.36280700e-01
-9.34231718e-01 -3.77388935e-02 -8.17667842e-01 -7.05972873e-01
-1.02469342e-02 -6.58013675e-01 3.99408077e-01 -6.98209243e-01
-8.05184213e-01 -6.21897340e-01 -6.81383532e-01 -8.84459652e-01
-7.78633095e-01 2.64120419e+00 -6.75786995e-01 -7.14756312e-01
5.39208100e+00 -9.62968205e-01 4.46201942e-01 1.49064599e-02
-7.65594438e-01 -7.57003906e-01 4.68797918e-01 4.26544994e-02
-7.17159179e-01 -9.55731852e-01 2.17599557e+00 -1.85007577e-01
-6.81849440e-01 -8.05928764e-01 -3.79880106e-01 2.59725911e-01
-6.51684996e-01 -6.88528960e-01 -3.30860487e-01 -8.49140578e-02
8.79507709e-01 -6.58710845e-01 -7.61537767e-01 -3.71613029e-02
-1.62755362e-02 -6.22033841e-01 4.01596604e-01 2.91696454e-01
4.27481323e-02 -7.81460130e-01 3.17022448e-01 -7.02173410e-01
-7.12650136e-01 2.41330409e+00 -3.79686072e-01 3.34195021e+00
6.57597849e-01 -7.01301383e-01 3.29792615e-01 2.96431650e+00
2.14601645e-01 -6.17344302e-01 -4.84580813e-01 -4.06814781e-01
-3.37247827e-01 2.70059368e-01 -2.79243967e-01 -9.67208871e-01
-3.89920255e-01 -7.68782468e-01 9.79130809e-01 2.78824757e-01
4.19759122e-01 -9.66507188e-01 -9.59379161e-02 -7.78661298e-01
-4.40742588e-01 -6.89279151e-01 -6.81535827e-01 -1.75300220e-01
-7.44309322e-01 -6.47526795e-01 -1.76389971e-01 -7.41718061e-01
3.97467734e-01 -3.83792380e-01 2.45494250e+00 -7.72924875e-01
1.76270241e+00 2.57537384e-01 -6.48693257e-01]
Unique values in p00r_1200: [-2.82517974e-01 -4.04765227e-01 -5.76372446e-01 -6.55143259e-01
-8.58730487e-02 -7.15787498e-01 1.90970674e-01 -4.99038342e-01
1.35828972e-01 -6.09035762e-01 2.57183371e-01 5.88264161e-02
-7.32310620e-01 -2.32547261e-01 3.06033413e-01 2.94429225e-01
-6.44386362e-01 -9.23068975e-01 -2.76175081e-02 -3.76040744e-01
5.02461184e-01 -7.10791009e-01 4.25185099e-02 -9.64011584e-02
-5.83674263e-01 -2.36708094e-01 2.05386235e-01 -6.07021267e-01
-6.32432207e-01 1.98096052e-01 -6.66768774e-01 2.41391207e-01
-4.98634086e-01 -6.11536915e-01 -6.20444122e-01 -6.47455607e-01
4.16084151e-01 -6.25207946e-01 2.03011109e-01 2.37905312e+00
2.58870196e-01 1.99491284e+00 -3.88007501e-01 2.72981561e+00
1.57825547e-01 1.44683069e+00 -6.22022517e-02 1.23652816e-01
-1.38157499e-03 -5.79800383e-01 -2.62081226e-01 -8.89442464e-01
-7.31538946e-01 -6.94450141e-01 2.49137026e-01 2.16466925e-01
-6.99067580e-01 -6.35594518e-01 3.64604843e-02 -6.53500060e-01
-5.89772035e-01 -8.93400199e-01 1.26599911e-01 7.22822322e-02
-5.86063930e-01 -6.32396338e-01 -5.97863944e-01 -5.86517628e-01
-6.57466036e-01 4.95713887e-01 -8.04121977e-02 -7.47536632e-01
-7.41060778e-01 1.80006316e-01 -5.91710914e-01 2.61582895e+00
-6.45534178e-01 2.59403387e-01 -6.79091316e-01 -1.59968256e-01
-4.23622759e-01 -7.20057878e-01 -8.26327803e-01 -3.72991857e-01
-5.89885459e-01 -5.92747244e-01 1.96397803e+00 1.78426131e-01
5.19057983e-01 -7.72177838e-01 3.02873041e-01 4.10711371e-02
3.71868029e-01 -6.85344199e-01 -2.30882882e-02 2.76504295e-01
2.81448435e-01 2.36803060e+00 3.97587251e-01 -6.42375745e-01
-7.14255784e-01 2.41018181e+00 -7.15772957e-01 -5.16043275e-01
-2.98871444e-01 -6.47610717e-01 3.14196091e-01 -3.39755604e-01
-5.65537994e-01 -2.47917720e-01 -2.47673421e-01 1.99754971e+00
-6.63166338e-01 -8.94009007e-01 -5.01999010e-01 -5.01724658e-01
3.04247558e-02 -5.89953468e-02 -6.94253345e-01 4.70372746e-01
-2.92485748e-01 -5.90020212e-01 2.20811191e+00 4.49655070e+00
-3.85854377e-01 1.96366781e+00 -3.94999097e-01 -6.34724931e-01
3.15010420e-01 2.98016151e-01 -8.35228806e-01 -8.45544900e-01
8.44469640e-01 2.77677316e-01 4.70615106e-01 2.62302010e-01
7.97946253e-01 1.40875112e+00 -1.18094299e-01 -6.86314608e-01
-4.45303297e-01 -5.86944181e-01 1.89603765e-01 3.01748491e-01
-4.29563482e-01 -4.27897985e-01 -6.64360687e-01 2.36921331e+00
1.79104738e-01 -4.59258374e-01 2.92393403e-01 1.29480323e+00
9.47036308e-01 1.83149447e+00 -7.81400113e-01 2.00810482e-01
-6.19872153e-01 -1.10019840e-01 -3.73803278e-01 -7.17276557e-01
5.14647035e-01 1.18718370e-01 -3.72737864e-01 -7.51281576e-01
3.00284638e-01 2.50028910e-01 2.97957984e-01 6.17446576e+00
3.36512581e-01 4.70644189e-01 -6.78922634e-01 2.12124046e+00
8.31205625e-02 -6.31235919e-01 -2.36530687e-01 -2.35544767e-01
-2.66928422e-01 3.28815234e-01 -6.16898883e-01 -3.70374371e-01
-5.21104718e-01 -2.34412462e-01 -5.33749113e-01 -6.01750426e-01
-3.63036834e-02 -6.84151789e-01 5.00347806e-01 -5.88560236e-01
-8.61964679e-01 -7.62659062e-02 -7.58062803e-01 -6.53057026e-01
-5.19882402e-02 -6.08931062e-01 2.97715624e-01 -6.48536531e-01
-7.48620465e-01 -5.74065181e-01 -6.33236842e-01 -8.23423363e-01
-7.23874560e-01 2.56592222e+00 -6.24841498e-01 -6.64051436e-01
5.74075805e+00 -8.86867246e-01 3.27215659e-01 -3.91402625e-02
-6.97421472e-01 -7.06386846e-01 3.21166359e-01 -6.38097296e-03
-6.63199299e-01 -8.81545509e-01 2.12752242e+00 -1.79682772e-01
-6.30845235e-01 -7.49867164e-01 -3.75398975e-01 2.49233970e-01
-5.98486324e-01 -6.34690031e-01 -3.18934958e-01 -8.87716719e-02
8.23907835e-01 -6.09014434e-01 -7.06958815e-01 -7.44957102e-02
-1.06727625e-01 -5.60041274e-01 2.73896503e-01 2.22884612e-01
-6.30244839e-03 -7.12149193e-01 2.24348466e-01 -6.47622350e-01
-6.60127146e-01 2.35971281e+00 -3.63598961e-01 3.63583410e+00
5.03168875e-01 -6.48998954e-01 2.36989953e-01 2.83344866e+00
1.41063944e-01 -5.89923268e-01 -4.61099339e-01 -4.00821548e-01
-3.37432827e-01 2.07887388e-01 -2.58650381e-01 -8.93100643e-01
-3.73412594e-01 -6.93835517e-01 9.14618261e-01 1.93559076e-01
3.14186396e-01 -8.90550242e-01 -9.49237331e-02 -7.23867774e-01
-4.61419254e-01 -6.35071021e-01 -6.27737213e-01 -2.17518045e-01
-6.77098149e-01 -5.95093287e-01 -1.98275646e-01 -6.83076681e-01
8.23956307e-01 2.93498564e-01 -3.78368367e-01 2.38483098e+00
-7.18363298e-01 1.68219114e+00 1.53307961e-01 -6.00271062e-01]
Unique values in p10r_1200: [-0.30872637 -0.361318 -0.52663565 -0.60973226 -0.06855705 -0.66565705
0.14046349 -0.51425322 0.07182578 -0.56481387 0.17659357 0.03344669
-0.70781225 -0.23440862 0.23941132 0.22730788 -0.59934647 -0.87152212
-0.02574346 -0.34782909 0.3861034 -0.65394418 0.01023554 -0.11186851
-0.5401091 -0.23140336 0.14435205 -0.56279062 -0.58765763 0.13827457
-0.62104168 0.20618264 -0.42666288 -0.56727405 -0.57595333 -0.60226417
0.34736378 -0.58055007 0.15263561 2.24832618 0.17879966 1.94604042
-0.38013328 2.99581282 0.05670076 1.38607139 -0.0716842 0.08307083
-0.0096536 -0.53631325 -0.2259096 -0.83829694 -0.68408176 -0.64816542
0.21251763 0.19116921 -0.65669621 -0.59066632 0.01292233 -0.60818628
-0.54602262 -0.84216292 0.08265021 0.03645109 -0.54243108 -0.58762329
-0.57014883 -0.54288259 -0.61207483 0.38061822 -0.09629197 -0.69992011
-0.6911258 0.12710678 -0.54791368 2.5222418 -0.60319382 0.19893774
-0.63313741 -0.16476744 -0.4323867 -0.67315175 -0.7767461 -0.36993119
-0.57243475 -0.57512069 1.87533397 0.13059188 0.47593502 -0.72395876
0.23863018 0.04105212 0.28953333 -0.63916424 -0.04636139 0.19582174
0.21199401 2.28433609 0.31307068 -0.59728116 -0.66741677 2.27280777
-0.6689782 -0.50404512 -0.2997123 -0.60529947 0.24263891 -0.33592651
-0.54734714 -0.24757391 -0.2473533 1.88396948 -0.61757289 -0.84275797
-0.48310959 -0.4828658 -0.05239337 -0.07171339 -0.64790447 0.37099555
-0.25533557 -0.57267939 2.34692207 4.76003201 -0.41777157 2.19812692
-0.39081092 -0.58991264 0.20148719 0.23026936 -0.78386825 -0.80325566
0.78287331 0.19427662 0.366137 0.1923023 0.89352114 1.35032759
-0.19143967 -0.64024582 -0.38847178 -0.54329033 0.14404302 0.23551419
-0.44766279 -0.44627047 -0.61873945 2.28537475 0.12633422 -0.47017778
0.24027831 1.24322495 0.92928211 1.95832413 -0.73294278 0.17900568
-0.57534988 -0.0486164 -0.3706986 -0.67046581 0.39719393 0.07722512
-0.36968998 -0.70356917 0.24314537 0.19092886 0.23021785 6.54503307
0.26195292 0.37121015 -0.63297431 2.01322743 0.05173921 -0.58644385
-0.29355586 -0.29266312 -0.3203225 0.255472 -0.57244848 -0.36742123
-0.50572844 -0.23601212 -0.53097143 -0.58271496 -0.09060936 -0.63813931
0.38731374 -0.54486035 -0.81143321 -0.09050807 -0.71020804 -0.60772102
-0.06949271 -0.56471 0.23000325 -0.60334404 -0.70105663 -0.53071305
-0.58846023 -0.77394428 -0.67685145 2.42310512 -0.58026422 -0.61847592
6.08676735 -0.83580329 0.24255307 -0.08198758 -0.65098441 -0.65978044
0.20438 -0.0243374 -0.61760465 -0.83057048 2.00975091 -0.15604609
-0.58607216 -0.70218028 -0.36834916 0.22198579 -0.55447959 -0.58979333
-0.31895164 -0.10065265 0.76316443 -0.56479327 -0.66032295 -0.09342663
-0.18021179 -0.51512707 0.17588968 0.19348689 -0.02426959 -0.6684357
0.16078183 -0.60241697 -0.61462085 2.28036169 -0.3609815 3.85475418
0.3922753 -0.60376809 0.17680817 2.6752002 0.09767222 -0.57259098
-0.4483787 -0.39245734 -0.33166197 0.18461962 -0.22423915 -0.84186703
-0.37032949 -0.64719972 0.84861821 0.13624874 0.24260457 -0.83938711
-0.07663631 -0.67680682 -0.47596598 -0.59015557 -0.58534338 -0.24705973
-0.63333312 -0.55119105 -0.20170184 -0.63705085 0.76320735 0.22275835
-0.36946422 2.30473168 -0.6714298 1.57921152 0.0720833 -0.55628824]
Unique values in p90_30: [ 1.29857984e+00 -6.22015462e-01 -4.96523920e-01 -5.80127837e-01
-6.15962460e-01 -4.89942688e-01 1.71977252e+00 -2.71507941e-01
1.33120766e+00 -6.97164754e-02 -3.57535594e-01 -5.52952574e-01
-1.47950564e-01 7.25683271e-01 7.98208264e-01 1.49589310e+00
-6.22806571e-01 -6.96301766e-01 -5.06428242e-01 -6.19939189e-01
-1.35094275e-01 -2.47239648e-01 -4.09112137e-02 5.62154495e-01
-5.39320486e-01 -4.66933117e-01 -1.98356679e-01 -4.73130856e-01
-6.52688241e-01 -3.71090830e-01 -5.71198948e-01 2.82715004e-01
-4.54577843e-01 -3.85454802e-01 -6.42532794e-01 -5.04597372e-01
8.92335811e-02 1.13299304e-01 3.67426720e-01 3.19164284e+00
-4.73321056e-01 -4.56693239e-01 -4.30570881e-01 -3.49964550e-02
-6.51698891e-01 5.25761781e+00 -4.53193867e-01 -4.06952051e-01
-4.16681636e-01 -6.21087038e-01 -6.43117620e-01 -5.72594831e-01
-6.30751831e-01 -6.70851422e-01 -2.48303531e-01 -3.57804658e-01
-5.91156040e-01 -5.01316034e-01 -5.22120522e-01 -1.18829849e-01
-5.60308988e-01 -4.93406494e-01 1.29721906e+00 1.49060461e+00
-4.98118199e-01 -6.52950501e-01 -6.75048040e-01 -2.23384227e-01
-3.82932718e-01 -2.95787060e-01 -2.93210853e-01 1.92662376e-02
-5.94212539e-01 -2.27788056e-02 -1.97193830e-01 -2.84367323e-01
-5.78581030e-01 6.04176343e-01 -5.52715056e-01 -4.70110850e-01
-6.64190089e-01 -2.91543897e-01 -3.09588163e-01 -3.04743473e-01
-4.69149025e-01 -3.96971958e-01 5.58802025e-01 -1.40204936e-01
-2.93345385e-01 -4.22618043e-01 6.00697073e-01 -4.32630609e-01
8.09838457e-02 -6.62654880e-01 -1.59115001e-02 -4.59625104e-01
4.98886048e-03 2.77949626e+00 -7.25772084e-02 -5.90394466e-01
9.67024137e-02 1.88307723e-01 -4.75124091e-01 1.93945687e-01
8.09818201e-01 -6.42470322e-01 2.14308369e+00 2.56351417e-01
-5.79345697e-01 1.05742483e-02 1.49411186e-02 -4.02778473e-01
-1.60118730e-01 -5.38057124e-01 -1.29751663e-01 -1.15383052e-01
-5.28197646e-01 -4.76489511e-01 7.68569524e-01 -2.32905056e-01
-6.45500534e-01 6.87927781e-01 -3.31162729e-01 4.39664094e-01
-6.21406667e-01 6.00555259e+00 -1.44440214e-02 -5.90430187e-01
-4.12662692e-01 1.16907369e+00 -3.83350077e-02 -6.21321309e-01
4.64630237e+00 -4.20550584e-01 -2.50854995e-01 1.01609406e+00
1.97384751e-01 6.51378886e+00 -4.18139836e-01 -5.79530639e-01
-5.52746911e-01 -5.53454981e-01 -5.18825113e-02 4.54977520e-01
-5.58116738e-01 -5.56571324e-01 6.42618409e-01 2.62766093e+00
-3.21527318e-02 -6.51963625e-01 2.23510202e-01 1.18326911e+00
-6.63994940e-01 4.42040975e-02 -5.43464528e-01 -1.03817805e-02
1.61489511e-01 8.36914755e-01 -3.99048696e-01 -2.77640734e-01
-2.51677650e-01 5.74297920e-01 -3.52791417e-01 -4.84999032e-01
5.28810719e-01 4.11019652e-01 1.16772837e+00 1.58746749e+00
1.62488897e+00 -2.30523689e-01 -5.55001168e-01 -1.26303320e-01
-5.21491161e-01 -5.79916452e-01 -4.74649364e-01 -5.14514065e-01
-3.97120407e-01 5.14296752e-01 -4.67299600e-01 -4.58327723e-01
-6.03234673e-01 8.31816465e-01 -5.89306924e-01 -3.54773827e-01
-6.53946345e-01 -1.69033393e-01 -3.87424842e-01 -5.32893888e-01
-6.82182460e-01 -4.90284429e-01 -4.52434613e-01 -2.42163006e-01
-4.36168639e-01 -3.20564100e-01 1.79249699e+00 2.00032538e+00
-3.17816250e-01 -3.77171047e-01 -5.76292908e-01 -6.67786726e-01
-5.59959824e-01 8.94845371e-01 -3.41308280e-01 1.12634377e-01
-1.38737458e-01 -2.86703846e-01 -4.90306078e-01 -5.55923561e-01
-5.43343759e-01 -6.85467169e-01 -5.00798010e-01 -3.35008482e-01
-1.98310289e-01 6.57879413e-02 9.87667805e-02 -6.00019054e-01
-5.60346873e-01 -1.28864063e-01 -5.29553789e-01 -3.47380766e-01
-1.69163286e-01 -2.68985857e-01 -3.96876085e-01 -2.98919795e-02
1.34251142e+00 -7.09612808e-02 2.63163054e-01 -4.10963262e-01
-5.47790420e-01 -6.52738961e-01 -4.64152793e-01 1.77166328e-01
-3.27720571e-01 -3.02439423e-01 9.39766611e-01 -2.92530463e-01
-2.61014463e-01 -4.11510667e-01 -4.00650706e-01 -1.45236734e-01
-3.02597150e-01 4.50323031e-01 8.55800232e-01 6.15973388e-01
5.27394270e-01 6.76543610e-01 -5.81594078e-01 -6.12174541e-01
-5.48498490e-01 -2.72578010e-01 -6.74076009e-01 -5.12336815e-01
-3.07860899e-01 -8.98684064e-02 -5.72739414e-01 9.32215975e-02
2.12930578e+00 9.54518715e-01 -4.77061658e-01 -4.94889436e-01
5.09904042e+00 -5.38896788e-01 -6.53549863e-01 -4.29392568e-01
-2.03713209e-01 -5.84139667e-01 3.13648186e-02 -6.79612842e-01
1.33058913e+00 -1.86916840e-01 -5.98811206e-01 -4.56894263e-01
-5.60895825e-01 -4.37650035e-01 -2.46234525e-01 6.39879991e-02]
Unique values in p00_30: [ 1.30754517e+00 -6.07961192e-01 -4.83533538e-01 -5.58128773e-01
-6.00079867e-01 -4.68393604e-01 1.57487283e+00 -3.31646662e-01
1.22049505e+00 -1.15402255e-01 -3.97800598e-01 -5.42892994e-01
-1.99378958e-01 6.20191335e-01 7.62003389e-01 1.41524632e+00
-6.04155086e-01 -6.72808395e-01 -4.91817496e-01 -4.54153950e-01
-1.53475775e-01 -2.49332014e-01 -6.49214962e-02 4.70487290e-01
-5.32651412e-01 -4.62325719e-01 -2.03284787e-01 -4.57568088e-01
-6.30330649e-01 -3.65855905e-01 -5.34192968e-01 2.54827372e-01
-4.14272946e-01 -3.92263185e-01 -6.21461509e-01 -4.80666494e-01
3.16674323e-02 2.06931109e-01 3.54529884e-01 3.32401928e+00
-4.77118007e-01 -4.28349164e-01 -4.25958576e-01 8.64210569e-02
-6.35531495e-01 5.23244598e+00 -4.44788271e-01 -4.09566560e-01
-4.07958522e-01 -6.05417971e-01 -6.23416085e-01 -5.47814753e-01
-5.99559089e-01 -6.49297879e-01 -2.36442779e-01 -3.51366942e-01
-5.54684164e-01 -4.67036260e-01 -5.14964379e-01 -1.10507504e-01
-5.46988158e-01 -4.75280051e-01 1.24883308e+00 1.36131264e+00
-4.85602797e-01 -6.30585636e-01 -6.53575177e-01 -2.55185217e-01
-3.84206375e-01 -2.77847334e-01 -3.07844653e-01 2.91147932e-02
-5.71441832e-01 -2.13978217e-02 -2.05928839e-01 -2.52640888e-01
-5.54929456e-01 5.64416931e-01 -5.41797700e-01 -4.60511310e-01
-6.43058803e-01 -2.90660391e-01 -1.94431575e-01 -3.08009473e-01
-4.37472460e-01 -3.78887799e-01 5.92421169e-01 -1.73988301e-01
-3.09688149e-01 -4.24347768e-01 5.67029127e-01 -4.33422587e-01
4.34223147e-02 -6.40557826e-01 -6.41431006e-02 -4.72335444e-01
-5.55982470e-03 3.26487783e+00 -8.00974414e-02 -5.62531002e-01
4.15566582e-02 1.85683124e-01 -4.58695515e-01 1.44252253e-01
7.10605730e-01 -6.05852044e-01 2.00143919e+00 2.13827251e-01
-5.71733107e-01 -2.70695836e-02 -2.31249736e-02 -3.99515284e-01
-1.59238950e-01 -5.21179079e-01 -1.46249992e-01 -1.32899537e-01
-5.36450869e-01 -4.79176185e-01 6.85816183e-01 -2.37282117e-01
-6.24993514e-01 6.12317350e-01 -2.73152029e-01 6.25671960e-01
-6.08462994e-01 7.24340761e+00 -6.40946240e-02 -5.76059158e-01
-4.18626144e-01 1.10736452e+00 -7.40974236e-02 -6.14399854e-01
3.88850849e+00 -4.48095760e-01 -2.69890247e-01 9.48222776e-01
2.23709552e-01 6.53574624e+00 -4.30943355e-01 -5.65787521e-01
-5.37420401e-01 -5.47987469e-01 -9.58121693e-02 4.30052268e-01
-5.62872554e-01 -5.61648174e-01 5.59283952e-01 3.09897706e+00
-3.05100370e-02 -6.32349768e-01 2.07915876e-01 1.23291891e+00
-6.40915306e-01 5.71024106e-02 -5.36043666e-01 -1.78230189e-02
2.66713834e-01 4.88182634e-01 -3.96570677e-01 -2.94465112e-01
-2.64172778e-01 5.20537300e-01 -3.52815700e-01 -4.65527945e-01
4.86301742e-01 3.68319398e-01 1.10599333e+00 1.92321181e+00
1.56028830e+00 -2.35132526e-01 -5.43883163e-01 -1.03506098e-01
-5.09371565e-01 -5.61396373e-01 -4.75721881e-01 -5.11166584e-01
-4.11858811e-01 4.83902843e-01 -4.36620657e-01 -4.54490516e-01
-5.91559204e-01 7.16726246e-01 -5.74192948e-01 -3.56729839e-01
-6.36150195e-01 -1.70324855e-01 -4.10477920e-01 -5.21262182e-01
-6.52231821e-01 -4.84516921e-01 -4.41199618e-01 -2.33444156e-01
-4.35133118e-01 -3.31354418e-01 1.69818344e+00 2.14135650e+00
-3.25139718e-01 -3.80130185e-01 -5.63144300e-01 -6.47074604e-01
-5.41592851e-01 9.27654848e-01 -3.52542846e-01 6.07132246e-02
-1.44898187e-01 -2.79840415e-01 -4.98187321e-01 -5.40723181e-01
-5.31306533e-01 -6.62781506e-01 -4.99586217e-01 -3.34052487e-01
-1.95815235e-01 7.31620149e-02 1.29422569e-01 -5.86288275e-01
-5.49676393e-01 -1.46510380e-01 -5.19018408e-01 -3.59459764e-01
-1.17065695e-01 -1.97667041e-01 -4.04987600e-01 -8.49367909e-02
1.06768296e+00 -1.16508906e-01 2.09235825e-01 -4.08387887e-01
-5.45193693e-01 -6.24822599e-01 -4.75244040e-01 1.32738369e-01
-3.27220056e-01 -2.42016203e-01 8.68416446e-01 -1.52546409e-01
-2.83538487e-01 -2.92733805e-01 -4.01585927e-01 -3.87787596e-02
-3.04156276e-01 3.77827736e-01 7.80507598e-01 5.72459891e-01
4.48336255e-01 6.01748067e-01 -5.68272432e-01 -5.96078331e-01
-5.39089243e-01 -2.70581385e-01 -6.52797474e-01 -4.84473984e-01
-3.10847432e-01 1.02061499e-02 -5.66468271e-01 7.06024506e-02
1.98821200e+00 1.16657522e+00 -4.65630438e-01 -4.88879815e-01
4.01702687e+00 -5.06623634e-01 -6.27274545e-01 -4.35063866e-01
-2.14340221e-01 -5.54209509e-01 -4.76342345e-03 -6.56684051e-01
1.05751673e+00 -1.87682247e-01 -5.84729960e-01 -3.92303351e-01
-5.49862959e-01 -4.46239799e-01 -1.95625484e-01 2.77647385e-01]
Unique values in p10_30: [ 1.23452916e+00 -5.82347135e-01 -4.56905896e-01 -5.34108149e-01
-5.74276058e-01 -4.45425443e-01 1.38857228e+00 -3.54079984e-01
1.12592350e+00 -9.13897934e-02 -4.13379556e-01 -5.23796697e-01
-2.36679204e-01 5.81524891e-01 7.20713311e-01 1.23658709e+00
-5.80354839e-01 -6.48576470e-01 -4.74863790e-01 -4.38625511e-01
-1.71169470e-01 -2.47485813e-01 -7.27404877e-02 4.39750264e-01
-5.08342694e-01 -4.46469463e-01 -2.24162259e-01 -4.33480702e-01
-6.06395478e-01 -3.69734007e-01 -5.09942604e-01 2.42523378e-01
-3.84975190e-01 -3.68720103e-01 -5.97402478e-01 -4.56484273e-01
2.26091386e-02 2.31754414e-01 3.54410429e-01 3.21997376e+00
-4.78535427e-01 -4.12021828e-01 -4.13814983e-01 2.05579884e-01
-6.17216392e-01 5.17119909e+00 -4.29526728e-01 -3.97845997e-01
-3.94227063e-01 -5.81374766e-01 -5.98116477e-01 -5.23733453e-01
-5.75208398e-01 -6.25153829e-01 -2.29383613e-01 -3.39875291e-01
-5.30589602e-01 -4.42643481e-01 -4.96983959e-01 -8.60542499e-02
-5.22772002e-01 -4.52097382e-01 1.17374513e+00 1.28640390e+00
-4.61560066e-01 -6.06648578e-01 -6.30286341e-01 -2.30942114e-01
-3.59932518e-01 -2.80863076e-01 -3.01257852e-01 5.46449868e-02
-5.47803380e-01 -5.78606958e-02 -1.80669800e-01 -2.41841580e-01
-5.30902808e-01 5.14597198e-01 -5.18092735e-01 -4.44631134e-01
-6.20344185e-01 -2.65562915e-01 -1.70826901e-01 -3.17189193e-01
-4.34861016e-01 -3.81641103e-01 5.76324870e-01 -1.73493418e-01
-3.18996150e-01 -4.00589059e-01 5.36116304e-01 -4.18663651e-01
-2.38459519e-03 -6.16337257e-01 -6.69594789e-02 -4.67620902e-01
-4.63024428e-02 3.25145748e+00 -1.13709481e-01 -5.38424770e-01
6.55519821e-02 1.82046774e-01 -4.34130704e-01 9.32348198e-02
6.67859808e-01 -5.81942201e-01 1.76520995e+00 1.95041809e-01
-5.57070185e-01 -3.40301908e-02 -3.02807542e-02 -3.84071711e-01
-1.33991323e-01 -4.97766974e-01 -1.47029022e-01 -1.34312560e-01
-5.33035268e-01 -4.72702970e-01 7.05856106e-01 -2.55017311e-01
-5.99700199e-01 5.18163430e-01 -2.27285535e-01 7.19822380e-01
-5.93014583e-01 8.34895947e+00 -9.60012992e-02 -5.51970927e-01
-4.34126940e-01 9.58955619e-01 -3.58697737e-02 -5.97911312e-01
3.67196406e+00 -4.57321245e-01 -2.86853641e-01 8.13106554e-01
2.96752176e-01 6.45460310e+00 -4.39845207e-01 -5.41759861e-01
-5.11816068e-01 -5.23757546e-01 -9.89589370e-02 4.00632147e-01
-5.53888811e-01 -5.52835506e-01 5.85598074e-01 3.08913247e+00
-6.57924857e-02 -6.10662156e-01 2.01860563e-01 1.22886987e+00
-6.17138593e-01 1.21511193e-01 -5.11735759e-01 -1.96046478e-02
2.91877156e-01 3.97374604e-01 -3.97685378e-01 -2.70345078e-01
-2.72881092e-01 4.88189270e-01 -3.57909730e-01 -4.41000907e-01
4.66589855e-01 2.91115473e-01 9.57700788e-01 2.08884355e+00
1.36729034e+00 -2.53073577e-01 -5.20169481e-01 -9.75698385e-02
-4.91807779e-01 -5.37014465e-01 -4.76503855e-01 -5.07481880e-01
-4.23649097e-01 3.95385696e-01 -4.12361888e-01 -4.50516294e-01
-5.74857171e-01 6.73368518e-01 -5.55948993e-01 -3.61849900e-01
-6.13685798e-01 -1.46941184e-01 -4.17763937e-01 -4.97227397e-01
-6.27911321e-01 -4.67763953e-01 -4.16569338e-01 -2.08937389e-01
-4.20298697e-01 -3.06526889e-01 1.49205823e+00 2.17370780e+00
-3.01276674e-01 -3.56285978e-01 -5.39082301e-01 -6.22682438e-01
-5.17390029e-01 9.00543213e-01 -3.28348409e-01 8.28021508e-02
-9.19281161e-02 -2.56220695e-01 -4.91048606e-01 -5.22854820e-01
-5.07010063e-01 -6.38600704e-01 -5.03314584e-01 -3.23027924e-01
-1.70634912e-01 9.75727723e-02 1.27885737e-01 -5.60186183e-01
-5.25903057e-01 -1.21800635e-01 -5.02368441e-01 -3.63890256e-01
-9.32996469e-02 -1.72928744e-01 -4.05760219e-01 -1.14764795e-01
1.00008900e+00 -9.24952999e-02 2.34048246e-01 -3.97105646e-01
-5.38532811e-01 -6.00705821e-01 -4.83094230e-01 1.25269413e-01
-3.16463900e-01 -2.18701233e-01 7.41229806e-01 -1.28028363e-01
-2.60356619e-01 -2.80703712e-01 -4.02524009e-01 2.13743844e-02
-3.04436340e-01 4.01082631e-01 6.62915772e-01 5.56340423e-01
4.16316286e-01 5.08567733e-01 -5.53844767e-01 -5.75642570e-01
-5.21483290e-01 -2.62292824e-01 -6.28084362e-01 -4.60593846e-01
-3.19770381e-01 3.67159543e-02 -5.47830987e-01 6.99953405e-02
1.75326396e+00 1.19128767e+00 -4.37147319e-01 -4.65072340e-01
3.41604118e+00 -4.82249728e-01 -6.03041690e-01 -4.42221858e-01
-1.89225241e-01 -5.30055922e-01 -1.30883079e-02 -6.32427083e-01
9.90451890e-01 -2.10913748e-01 -5.64785391e-01 -3.77246683e-01
-5.26055645e-01 -4.34000202e-01 -2.47802030e-01 3.03836955e-01]
Unique values in p90u_30: [ 1.45281061e+00 -5.47467181e-01 -4.19957086e-01 -4.83903172e-01
-5.58541728e-01 -3.69232347e-01 1.84524601e+00 -1.58817476e-01
1.47359348e+00 -1.97710492e-02 -4.39569500e-01 -5.26087388e-01
-6.11182484e-03 5.20119148e-01 6.09624156e-01 1.19569777e+00
-5.19928541e-01 -5.68857695e-01 -5.22592223e-01 -5.00986892e-01
-3.37358039e-01 -8.98714715e-02 -9.73309183e-02 4.43902481e-01
-4.36190780e-01 -4.76732247e-01 -3.05690891e-01 -4.12059595e-01
-5.31560433e-01 -4.86598263e-01 -4.41491581e-01 3.07819785e-01
-3.48628235e-01 -2.92997302e-01 -5.39218687e-01 -4.50864088e-01
-1.31674445e-01 2.13476579e-01 3.80469618e-01 2.64988058e+00
-4.68269074e-01 -5.54303459e-01 -3.87128336e-01 -3.82960068e-01
-5.68837162e-01 5.82100583e+00 -4.77873300e-01 -5.45557296e-01
-3.81778919e-01 -5.30423724e-01 -5.67414021e-01 -4.46410974e-01
-5.28043717e-01 -5.68852032e-01 -3.10829807e-01 -3.28597157e-01
-4.81981926e-01 -4.12993989e-01 -5.15067788e-01 -9.13132414e-02
-4.64752692e-01 -3.50922036e-01 1.10523214e+00 1.52723802e+00
-3.98162971e-01 -5.31705111e-01 -5.54882222e-01 -9.15805452e-02
-2.77827811e-01 -3.70228053e-01 -2.73961930e-01 1.21793045e-01
-4.74917922e-01 -1.14376548e-01 -7.62840851e-02 -3.06036716e-01
-4.75980789e-01 3.51453790e-01 -4.80452280e-01 -3.87388958e-01
-5.59718717e-01 -1.59086450e-01 -1.77657382e-01 -3.54971689e-01
-5.02698305e-01 -4.78010961e-01 2.42664483e-01 -2.15014759e-01
-4.34993593e-01 -3.29238686e-01 3.67381755e-01 -4.02913127e-01
-3.18815821e-02 -5.63886200e-01 3.22145286e-02 -4.19518039e-01
-1.13315686e-01 1.75544864e+00 -2.90660064e-01 -5.03342173e-01
7.33976914e-02 -2.78369414e-02 -3.57171933e-01 3.63188427e-01
9.81298400e-01 -5.36883788e-01 2.17376238e+00 2.91472487e-01
-5.19063980e-01 -1.80759776e-01 -1.82256678e-01 -5.68858168e-01
-7.75521075e-02 -4.01063218e-01 1.33612572e-02 2.90553317e-02
-4.82288991e-01 -4.59344969e-01 8.95522280e-01 -3.42799342e-01
-5.67021306e-01 5.11042513e-01 -4.99203809e-01 2.59562783e-02
-5.06600439e-01 6.60098162e+00 -1.10412098e-01 -4.98290799e-01
-4.93385775e-01 8.35500882e-01 1.13197557e-01 -5.26634358e-01
5.06981532e+00 -5.16837841e-01 -3.02269403e-01 1.07857025e+00
-2.09494935e-01 6.75471472e+00 -3.34646576e-01 -4.80252136e-01
-5.39644535e-01 -4.43090893e-01 -4.91293600e-02 2.20393065e-01
-4.30020406e-01 6.83009074e-01 1.60614276e+00 -1.25204022e-01
-5.49896639e-01 9.44796082e-02 9.75579769e-01 -5.46951452e-01
-2.21364895e-01 -4.78917121e-01 -4.64746991e-02 2.30610752e-01
6.11869508e-01 -4.48453342e-01 -2.02987758e-01 -4.04467499e-01
4.55080792e-01 -3.96980152e-01 -4.32039385e-01 3.17193796e-01
3.85763591e-02 8.34353146e-01 -2.07171063e-01 1.11931571e+00
-3.41461152e-01 -4.81052711e-01 -3.35212926e-01 -4.95247546e-01
-5.44559250e-01 -4.12430813e-01 -4.55271928e-01 -2.54079539e-01
6.73716613e-02 -4.01739830e-01 -4.96926715e-01 -5.34336550e-01
6.40417554e-01 -4.93147707e-01 -3.81112330e-01 -5.41720651e-01
-5.31659603e-03 -4.88936002e-01 -4.50500221e-01 -5.58665757e-01
-4.80009558e-01 -3.31047998e-01 -2.93550287e-01 -3.89671064e-01
-1.93191074e-01 1.56141949e+00 2.16985307e+00 -1.64063313e-01
-3.17042950e-01 -4.75343269e-01 -5.57792776e-01 -4.65012645e-01
2.53512006e-01 -2.14535283e-01 2.78087249e-01 -5.15662038e-01
-1.76626591e-01 -5.68787099e-01 -4.50402655e-01 -4.44688869e-01
-5.57523601e-01 -4.98807030e-01 -2.80911829e-01 -1.18553170e-01
2.37071151e-01 -2.24032921e-01 -5.28934842e-01 -4.96855378e-01
-3.48687021e-02 -4.83400140e-01 -4.03969144e-01 -5.02186230e-02
-2.02596827e-01 -4.14604828e-01 -4.68188527e-02 1.47337630e+00
-2.08135340e-02 4.65201582e-01 -4.42893757e-01 -4.37991572e-01
-5.29390929e-01 -4.29430500e-01 1.71932556e-01 -2.72906080e-01
-1.45166604e-01 1.02285245e+00 -1.59791464e-01 -2.00759113e-01
-5.40942462e-01 -4.59766307e-01 -3.54204861e-01 -2.98273211e-01
5.44807996e-01 9.38239098e-01 4.01586618e-01 4.79567491e-01
5.08967568e-01 -5.10846560e-01 -5.46337154e-01 -5.59863729e-01
-2.90349324e-01 -5.68845996e-01 -4.06438196e-01 -3.58860959e-01
8.54079854e-02 -5.33536309e-01 1.40910279e-01 2.15862631e+00
1.21198659e+00 -3.93062481e-01 -4.46240401e-01 5.59613651e+00
-4.47330332e-01 -5.44919609e-01 -3.25090465e-01 -4.55157467e-02
-5.12893940e-01 8.76082298e-02 -5.68825099e-01 1.46151469e+00
-2.83274126e-01 -5.24235975e-01 -4.65185390e-01 -4.82079158e-01
-4.86625996e-01 -1.09281069e-01 2.51079541e-01]
Unique values in p00u_30: [ 1.46484044e+00 -5.34147707e-01 -4.10897116e-01 -4.68648227e-01
-5.43569604e-01 -3.53450137e-01 1.71024240e+00 -2.21316070e-01
1.36918268e+00 -6.07560876e-02 -4.47007619e-01 -5.13894920e-01
-6.31520552e-02 4.44815683e-01 5.88931095e-01 1.14062336e+00
-5.06795981e-01 -5.52943814e-01 -5.08503466e-01 -3.57961613e-01
-3.37050802e-01 -9.78340247e-02 -1.12285222e-01 3.74835035e-01
-4.33635134e-01 -4.67736583e-01 -3.03134819e-01 -4.00354708e-01
-5.16390104e-01 -4.74787272e-01 -4.11127967e-01 2.80002066e-01
-3.15933417e-01 -3.01830532e-01 -5.24462208e-01 -4.33820147e-01
-1.57980500e-01 3.05169526e-01 3.75145651e-01 2.78731199e+00
-4.63911177e-01 -5.37852183e-01 -3.82323883e-01 -3.37925353e-01
-5.52926701e-01 5.83317631e+00 -4.67088360e-01 -5.31695346e-01
-3.74368487e-01 -5.18202385e-01 -5.51600398e-01 -4.28351038e-01
-5.07060457e-01 -5.52938512e-01 -2.99695422e-01 -3.23195204e-01
-4.54488948e-01 -3.87277158e-01 -5.03834269e-01 -8.88020262e-02
-4.56026197e-01 -3.39213054e-01 1.07008631e+00 1.41177933e+00
-3.91114626e-01 -5.16531993e-01 -5.40225337e-01 -1.28162842e-01
-2.82813576e-01 -3.55506839e-01 -2.84209842e-01 1.29665280e-01
-4.59032692e-01 -1.09922427e-01 -8.86949691e-02 -2.82869366e-01
-4.60467558e-01 3.29334269e-01 -4.71682315e-01 -3.81333228e-01
-5.44177900e-01 -1.63162967e-01 -6.55178658e-02 -3.51998081e-01
-4.62680323e-01 -4.47579846e-01 2.71340998e-01 -2.33184327e-01
-4.31432925e-01 -3.33849645e-01 3.49204666e-01 -4.01898742e-01
-5.40567271e-02 -5.48079572e-01 -1.20813057e-02 -4.25406667e-01
-1.16219193e-01 2.10642898e+00 -2.86581684e-01 -4.84225333e-01
3.00313297e-02 -2.39103588e-02 -3.46485396e-01 3.09260313e-01
8.82627863e-01 -5.12958096e-01 2.04768329e+00 2.52598470e-01
-5.09553379e-01 -1.95534917e-01 -1.96925151e-01 -5.52944216e-01
-7.88019905e-02 -3.91003046e-01 -7.82465598e-03 6.86930485e-03
-4.82580575e-01 -4.55743627e-01 8.15542279e-01 -3.39045683e-01
-5.51154885e-01 4.57288586e-01 -4.76087940e-01 1.31272644e-01
-4.99065555e-01 7.98167615e+00 -1.40555830e-01 -4.87984092e-01
-4.84784895e-01 7.97496376e-01 7.24078382e-02 -5.19763759e-01
4.29802306e+00 -5.10147621e-01 -3.10393590e-01 1.01842750e+00
-1.89711615e-01 6.82119251e+00 -3.47669055e-01 -4.71139490e-01
-5.25190648e-01 -4.42242373e-01 -8.40975462e-02 2.10699949e-01
-4.41431453e-01 6.08309934e-01 1.94038496e+00 -1.20493937e-01
-5.35617706e-01 8.71078304e-02 1.02311691e+00 -5.31501437e-01
-2.07933936e-01 -4.72140549e-01 -4.96568320e-02 3.29430771e-01
3.36311073e-01 -4.39953160e-01 -2.19655932e-01 -4.00725638e-01
4.14705503e-01 -3.91453892e-01 -4.17722532e-01 2.91627560e-01
2.25297951e-02 7.96312717e-01 -1.38939419e-01 1.08615995e+00
-3.37819804e-01 -4.72234187e-01 -3.18073051e-01 -4.83613298e-01
-5.29995099e-01 -4.12799867e-01 -4.51181488e-01 -2.76319283e-01
5.95519419e-02 -3.80059098e-01 -4.86458604e-01 -5.22503667e-01
5.55073918e-01 -4.82629580e-01 -3.77878753e-01 -5.29263341e-01
-1.18355268e-02 -4.85198497e-01 -4.42392705e-01 -5.38163674e-01
-4.71115666e-01 -3.25404199e-01 -2.85664913e-01 -3.88344713e-01
-2.08989428e-01 1.49207214e+00 2.32901723e+00 -1.78312298e-01
-3.20478065e-01 -4.66860072e-01 -5.42891435e-01 -4.52288247e-01
2.78121782e-01 -2.30854705e-01 2.20882434e-01 -5.05293563e-01
-1.74186831e-01 -5.52880001e-01 -4.40828465e-01 -4.37225919e-01
-5.42415846e-01 -4.90284311e-01 -2.80925753e-01 -1.18370889e-01
2.41915380e-01 -2.02243324e-01 -5.16162570e-01 -4.87210567e-01
-5.56535362e-02 -4.73541640e-01 -4.05138500e-01 -2.17324857e-03
-1.42237078e-01 -4.13965884e-01 -8.83391174e-02 1.20383227e+00
-6.16909522e-02 4.04943707e-01 -4.35390116e-01 -4.39743268e-01
-5.09265380e-01 -4.32876989e-01 1.34065176e-01 -2.73363904e-01
-8.61029816e-02 9.57932716e-01 -2.06202385e-02 -2.20996407e-01
-5.14999116e-01 -4.52111829e-01 -3.04148091e-01 -2.97712604e-01
4.75694864e-01 8.69069310e-01 3.74966217e-01 4.14975407e-01
4.55347988e-01 -4.99917187e-01 -5.32078942e-01 -5.44757893e-01
-2.86691756e-01 -5.52933186e-01 -3.85987950e-01 -3.55628975e-01
1.89443842e-01 -5.23015279e-01 1.20447817e-01 2.03308734e+00
1.44677644e+00 -3.84971661e-01 -4.40163505e-01 4.47504420e+00
-4.23731148e-01 -5.27270119e-01 -3.34160261e-01 -6.21900493e-02
-4.93392585e-01 5.51113349e-02 -5.52912133e-01 1.19362415e+00
-2.78881113e-01 -5.12333244e-01 -4.30769322e-01 -4.73721074e-01
-4.80364493e-01 -6.20483118e-02 4.80277209e-01]
Unique values in p10u_30: [ 1.37919773e+00 -5.12303407e-01 -3.88234005e-01 -4.47665867e-01
-5.21872123e-01 -3.33992722e-01 1.51107055e+00 -2.46333684e-01
1.26201523e+00 -4.15683184e-02 -4.41133300e-01 -4.94068640e-01
-1.07023211e-01 4.13715955e-01 5.56720770e-01 9.91019651e-01
-4.85781532e-01 -5.31400340e-01 -4.88937910e-01 -3.45017262e-01
-3.33799571e-01 -1.02236616e-01 -1.15802037e-01 3.47967256e-01
-4.12584025e-01 -4.49940962e-01 -3.07099916e-01 -3.79544953e-01
-4.95301539e-01 -4.60921839e-01 -3.90200875e-01 2.65274361e-01
-2.90682125e-01 -2.81988992e-01 -5.03168477e-01 -4.12852667e-01
-1.56714576e-01 3.23657498e-01 3.74277889e-01 2.68779231e+00
-4.54366965e-01 -5.16862166e-01 -3.69852063e-01 -2.90567867e-01
-5.31386040e-01 5.73516298e+00 -4.49292956e-01 -5.11215507e-01
-3.60666533e-01 -4.96934749e-01 -5.30035193e-01 -4.07545245e-01
-4.85667954e-01 -5.31395040e-01 -2.89184528e-01 -3.11727367e-01
-4.33494742e-01 -3.66361752e-01 -4.84450290e-01 -6.87440484e-02
-4.34956564e-01 -3.19774397e-01 1.00142529e+00 1.32998516e+00
-3.70487283e-01 -4.95441505e-01 -5.19378985e-01 -1.08486802e-01
-2.62425024e-01 -3.48474928e-01 -2.76799773e-01 1.49479281e-01
-4.38500060e-01 -1.31915141e-01 -6.81469142e-02 -2.71109995e-01
-4.39505667e-01 2.95496972e-01 -4.50846049e-01 -3.67233649e-01
-5.23141108e-01 -1.42473128e-01 -4.67425752e-02 -3.49629750e-01
-4.49816230e-01 -4.36149065e-01 2.63153786e-01 -2.28188419e-01
-4.21593815e-01 -3.13711920e-01 3.27078438e-01 -3.86978526e-01
-8.32303353e-02 -5.26548079e-01 -1.71959908e-02 -4.16767637e-01
-1.38906645e-01 2.09317444e+00 -2.92072264e-01 -4.63090974e-01
4.88342730e-02 -2.17649521e-02 -3.25545788e-01 2.48010516e-01
8.28812684e-01 -4.91808507e-01 1.80589709e+00 2.31794036e-01
-4.92288527e-01 -1.92724901e-01 -1.94044309e-01 -5.31400686e-01
-5.84118574e-02 -3.71074896e-01 -1.43953087e-02 -4.58548582e-04
-4.72051252e-01 -4.43502522e-01 8.27014480e-01 -3.38949344e-01
-5.29581861e-01 3.81813479e-01 -4.50747977e-01 1.86523369e-01
-4.85071636e-01 9.12730728e+00 -1.58665124e-01 -4.66851423e-01
-4.74139590e-01 6.82722902e-01 1.05753819e-01 -5.02724503e-01
4.04369516e+00 -4.95059557e-01 -3.16656785e-01 8.79400430e-01
-1.50068567e-01 6.70371748e+00 -3.54948190e-01 -4.50143090e-01
-5.03498057e-01 -4.21219892e-01 -8.67451302e-02 1.95153932e-01
-4.35723726e-01 6.26767748e-01 1.93084642e+00 -1.41296542e-01
-5.15259153e-01 8.39590980e-02 1.01457857e+00 -5.10395842e-01
-1.68995955e-01 -4.50895425e-01 -5.02165636e-02 3.48085594e-01
2.59738287e-01 -4.29204760e-01 -1.99693281e-01 -3.92056208e-01
3.86500779e-01 -3.85323145e-01 -3.96536075e-01 2.77661837e-01
-1.42348034e-02 6.81655133e-01 -9.67440687e-02 9.41970308e-01
-3.37846210e-01 -4.51393127e-01 -3.05081358e-01 -4.65200259e-01
-5.08507456e-01 -4.09516196e-01 -4.42896954e-01 -2.93999688e-01
1.90129253e-02 -3.59257350e-01 -4.71348429e-01 -5.03891839e-01
5.18160043e-01 -4.65654843e-01 -3.73283884e-01 -5.08977682e-01
6.42005731e-03 -4.72076552e-01 -4.21508938e-01 -5.16654190e-01
-4.53175825e-01 -3.04501906e-01 -2.65165856e-01 -3.74012960e-01
-1.88354531e-01 1.30698393e+00 2.34684089e+00 -1.58826989e-01
-3.00218590e-01 -4.45860998e-01 -5.21350385e-01 -4.31241818e-01
2.69576720e-01 -2.10785832e-01 2.36796906e-01 -4.81387630e-01
-1.54848361e-01 -5.31343015e-01 -4.25166419e-01 -4.16170775e-01
-5.21023308e-01 -4.79092540e-01 -2.71142640e-01 -9.78852888e-02
2.60173556e-01 -1.93441734e-01 -4.94014776e-01 -4.66222188e-01
-3.58010079e-02 -4.56255079e-01 -3.97705588e-01 1.64924474e-02
-1.22015498e-01 -4.05944680e-01 -1.11355495e-01 1.12550408e+00
-4.24987052e-02 4.22949092e-01 -4.20098531e-01 -4.34289243e-01
-4.88058395e-01 -4.31252700e-01 1.25704088e-01 -2.63907658e-01
-6.76137100e-02 8.25167309e-01 -1.13321509e-03 -2.01709119e-01
-4.94780985e-01 -4.40325060e-01 -2.69650484e-01 -2.92813581e-01
4.91822205e-01 7.46344225e-01 3.62551478e-01 3.83991182e-01
3.80058802e-01 -4.83573903e-01 -5.11669003e-01 -5.23649570e-01
-2.76821537e-01 -5.31389473e-01 -3.65540182e-01 -3.52914669e-01
2.10200627e-01 -5.03185071e-01 1.16657300e-01 1.79277102e+00
1.46018492e+00 -3.60771269e-01 -4.19397884e-01 3.80767070e+00
-4.02674996e-01 -5.05863878e-01 -3.42315876e-01 -4.18866086e-02
-4.72169455e-01 4.45999246e-02 -5.31368795e-01 1.11587376e+00
-2.85222223e-01 -4.92948231e-01 -4.13748640e-01 -4.52859983e-01
-4.62968691e-01 -1.20870197e-01 4.99443488e-01]
Unique values in p90r_30: [-2.14494329e-01 -5.35976477e-01 -5.01247959e-01 -6.14765912e-01
-4.60178500e-01 -6.88934800e-01 5.49877831e-02 -5.78861229e-01
-1.52262516e-01 -2.39045708e-01 2.29327732e-01 -3.06891627e-01
-6.61553003e-01 1.13563666e+00 1.08765543e+00 1.80926465e+00
-6.58161103e-01 -7.89299972e-01 -1.05627838e-01 -7.26341539e-01
8.23665201e-01 -7.62732218e-01 2.28630373e-01 7.03338284e-01
-6.30363766e-01 -1.19356480e-01 3.93279178e-01 -4.26478767e-01
-7.47032276e-01 3.68691853e-01 -7.55762358e-01 -1.02405204e-02
-6.13187866e-01 -5.31210706e-01 -6.66861565e-01 -4.05784435e-01
9.81498572e-01 -3.91893316e-01 7.09767335e-02 3.43545737e+00
-1.85477691e-01 2.62060507e-01 -3.35892448e-01 1.48528711e+00
-5.82020197e-01 -6.05709581e-01 -5.05723603e-02 4.55674906e-01
-2.94339151e-01 -6.05002875e-01 -5.48247853e-01 -7.41082790e-01
-6.60178414e-01 -6.70999712e-01 1.83172579e-01 -2.49462250e-01
-6.74306061e-01 -5.53493149e-01 -2.10968708e-01 -1.59521528e-01
-6.05033789e-01 -7.83835547e-01 1.27495764e+00 3.57979831e-01
-6.02449963e-01 -7.47628986e-01 -7.50627346e-01 -6.44469845e-01
-5.84762187e-01 2.18019001e-01 -1.84261266e-01 -4.34540822e-01
-7.18914801e-01 3.86291201e-01 -5.88523616e-01 -5.12175572e-03
-6.41666027e-01 1.29653985e+00 -5.02167468e-01 -5.18601434e-01
-6.79333522e-01 -6.70855927e-01 -6.74831597e-01 1.10726242e-01
-1.79186675e-02 2.11412056e-01 1.55373621e+00 2.73426753e-01
5.08077541e-01 -5.48033612e-01 1.21182142e+00 -2.77539969e-01
5.13706744e-01 -6.54262358e-01 -2.12602831e-01 -3.31593980e-01
5.10823845e-01 5.36826554e+00 9.13365801e-01 -5.78846850e-01
1.33739115e-01 9.95266036e-01 -6.71935756e-01 -6.61206480e-01
-4.57787346e-01 -6.76618851e-01 6.09288172e-01 -6.24562339e-02
-4.59822630e-01 8.27029782e-01 8.53773890e-01 5.75354788e-01
-4.10702619e-01 -7.75653072e-01 -6.60743491e-01 -6.61473203e-01
-3.80275445e-01 -2.38609319e-01 -2.80440842e-01 3.92337382e-01
-5.61016726e-01 9.99169813e-01 6.08569245e-01 1.93239539e+00
-7.09007259e-01 -4.84773014e-01 4.07981248e-01 -6.00749699e-01
2.04618190e-01 1.83984783e+00 -6.65347503e-01 -6.22398767e-01
-2.15223322e-01 2.68868752e-01 1.34472421e-01 8.26377396e-02
1.81920023e+00 1.21655196e+00 -5.03941062e-01 -6.27701577e-01
-2.47595914e-01 -6.66384197e-01 -2.98025411e-02 1.16687406e+00
-7.44304521e-01 -7.37119774e-01 4.84886774e-02 5.30482018e+00
3.89310697e-01 -6.64757264e-01 6.32574238e-01 1.30308209e+00
-7.33367547e-01 1.15811033e+00 -4.65767443e-01 1.51726685e-01
-2.41582803e-01 1.25794062e+00 7.45569931e-02 -4.17295186e-01
5.70437323e-01 7.11699413e-01 6.81154016e-02 -3.95676313e-01
1.09357220e+00 1.74490625e+00 1.83856814e+00 8.27202860e+00
2.73776687e+00 3.97643068e-01 -5.10213706e-01 8.55305206e-01
-2.93334809e-01 -3.52762804e-01 -4.31938304e-01 -4.32918921e-01
-7.52919718e-01 2.10115646e+00 -4.43774009e-01 7.54574905e-03
-5.05165396e-01 1.11138723e+00 -6.17659596e-01 -9.38499655e-03
-7.09159672e-01 -7.62987653e-01 3.02809325e-01 -5.38908983e-01
-7.67515099e-01 -2.13817100e-01 -6.78876284e-01 1.37362511e-01
-3.50975550e-01 -6.59010875e-01 1.61451435e+00 -3.75238238e-02
-7.71589118e-01 -3.89220343e-01 -6.33772202e-01 -7.04342857e-01
-6.02291799e-01 3.06938662e+00 -6.63604823e-01 -6.73024213e-01
1.57402434e+00 -5.72871843e-01 1.68118234e-01 -6.46396571e-01
-6.12498415e-01 -7.87701451e-01 -1.81809723e-01 -3.48683609e-01
-4.11817676e-01 -7.14322291e-01 1.42326522e+00 -5.13460383e-01
-4.67062951e-01 -4.49062441e-01 -3.81799572e-01 1.23350611e-01
-5.70374288e-01 -3.78740535e-01 -6.09968108e-02 6.25005768e-02
-9.87635169e-02 -2.40344091e-01 -7.78391755e-01 -4.75510264e-03
-6.61992987e-01 -7.56603791e-01 -3.09985172e-01 8.38024024e-02
-3.49250124e-01 -7.81409238e-01 -3.24338162e-02 -6.72409530e-01
-3.49581549e-01 4.14631328e-01 1.15794682e-01 8.49007400e-01
-1.23285419e-01 -2.50816710e-01 -5.86818639e-02 1.13565103e+00
3.88253874e-01 9.55164253e-01 -5.05637731e-01 -4.95086749e-01
-1.40834443e-01 -1.78108283e-02 -6.86018111e-01 -6.32948311e-01
1.12969296e-01 -7.85350982e-01 -3.66829342e-01 -1.72969789e-01
6.10438456e-01 -7.77744936e-01 -5.26499573e-01 -3.80548638e-01
-3.75173216e-01 -5.80459405e-01 -6.93550315e-01 -5.97382961e-01
-7.51241166e-01 -5.08662979e-01 -2.31178483e-01 -7.11849899e-01
-1.03153289e-01 3.49985356e-01 -5.28066116e-01 -1.22373819e-01
-5.33201416e-01 5.93588631e-02 -6.74536117e-01 -7.82973841e-01]
Unique values in p00r_30: [-1.65937436e-01 -5.12415908e-01 -4.63430960e-01 -5.57547809e-01
-4.40189260e-01 -6.27790764e-01 1.70911064e-02 -5.60639805e-01
-1.62437690e-01 -2.60297482e-01 5.59180193e-02 -3.09463921e-01
-6.17483301e-01 9.24248228e-01 9.65464769e-01 1.60525582e+00
-6.05530323e-01 -7.20247020e-01 -1.08004391e-01 -5.47490803e-01
6.81933930e-01 -6.96524502e-01 1.66941937e-01 5.51133574e-01
-5.86743614e-01 -1.42748368e-01 3.28299279e-01 -3.92317455e-01
-6.81368334e-01 3.06907574e-01 -6.83779741e-01 -1.03502891e-02
-5.41919643e-01 -5.02365558e-01 -6.10243032e-01 -3.58937683e-01
7.72159012e-01 -3.20536064e-01 4.34012099e-02 3.33576976e+00
-2.22707731e-01 2.86967794e-01 -3.26589384e-01 1.73327937e+00
-5.57495176e-01 -5.48882232e-01 -6.87540000e-02 3.44306760e-01
-2.79890614e-01 -5.65281733e-01 -5.09898632e-01 -6.74175615e-01
-5.84394520e-01 -6.17577676e-01 1.69670347e-01 -2.38015867e-01
-5.99311241e-01 -4.86134843e-01 -2.27840893e-01 -1.26394845e-01
-5.59528477e-01 -7.14992816e-01 1.16143239e+00 2.81795309e-01
-5.51838716e-01 -6.81913593e-01 -6.87267569e-01 -6.00407445e-01
-5.43473809e-01 2.12744143e-01 -2.04334821e-01 -3.93067617e-01
-6.54276308e-01 3.47561493e-01 -5.43612347e-01 3.14107236e-02
-5.76395619e-01 1.14396088e+00 -4.74042117e-01 -4.81485656e-01
-6.25474942e-01 -6.14936986e-01 -5.86382448e-01 6.69224061e-02
-5.44827804e-02 1.40825424e-01 1.49895671e+00 1.75611143e-01
3.78293920e-01 -5.14040855e-01 1.07564778e+00 -2.80657715e-01
4.06545974e-01 -5.98896837e-01 -2.31695151e-01 -3.56303043e-01
4.42003209e-01 5.80925221e+00 7.99951290e-01 -5.14278608e-01
6.10179083e-02 9.06970312e-01 -6.13373141e-01 -6.10717327e-01
-4.37396723e-01 -5.88219134e-01 5.26414539e-01 -7.94982501e-02
-4.52852472e-01 6.66277331e-01 6.89084664e-01 4.73461599e-01
-3.79370513e-01 -7.07679889e-01 -6.07406937e-01 -6.08050624e-01
-4.06963150e-01 -2.64471768e-01 -2.76514887e-01 3.23883005e-01
-5.18575703e-01 8.39812700e-01 7.17040283e-01 2.20616552e+00
-6.55362227e-01 -3.85397214e-01 2.83973197e-01 -5.58287081e-01
1.16523817e-01 1.63716189e+00 -6.14160811e-01 -5.98249520e-01
-2.59771764e-01 8.95603475e-02 6.64989277e-02 5.56215844e-02
1.73828247e+00 1.17967826e+00 -4.87406488e-01 -5.81004878e-01
-2.40240338e-01 -6.19195968e-01 -8.10772193e-02 1.03305191e+00
-6.87465393e-01 -6.82117649e-01 2.25121593e-03 5.75081220e+00
3.50174959e-01 -6.13044038e-01 5.58659389e-01 1.28033905e+00
-6.66972249e-01 1.08367572e+00 -4.47071388e-01 1.21381719e-01
-1.56752796e-01 7.82987958e-01 3.29836431e-02 -4.04889317e-01
4.53896901e-01 6.09779273e-01 2.95171705e-02 -3.57399247e-01
9.54049003e-01 1.51837622e+00 1.63587936e+00 8.95775307e+00
2.45727607e+00 3.28353726e-01 -4.80937554e-01 8.24053256e-01
-2.84542826e-01 -3.25687980e-01 -4.21678417e-01 -4.22502385e-01
-6.90310986e-01 1.87469693e+00 -3.82249560e-01 -3.34177585e-02
-4.87491789e-01 9.03534088e-01 -5.71618178e-01 -4.20446170e-02
-6.55138994e-01 -6.96469450e-01 1.53771761e-01 -5.01859199e-01
-6.89671353e-01 -2.26123991e-01 -6.21534174e-01 1.26475558e-01
-3.42510354e-01 -6.08815305e-01 1.43103079e+00 8.79698092e-03
-7.04755953e-01 -3.74550724e-01 -5.86629275e-01 -6.48177010e-01
-5.50959696e-01 2.93600017e+00 -6.13633278e-01 -6.21026605e-01
1.39441806e+00 -5.23448124e-01 4.22215203e-02 -5.93139347e-01
-5.66465052e-01 -7.18690610e-01 -2.15036118e-01 -3.31981473e-01
-3.80373551e-01 -6.51033069e-01 1.37672877e+00 -4.89910455e-01
-4.46154860e-01 -4.16648100e-01 -3.67085406e-01 5.53977459e-02
-5.02611780e-01 -2.92706278e-01 -1.08040689e-01 -1.65633211e-02
-1.66412337e-01 -2.61382191e-01 -7.10777633e-01 -3.69386783e-02
-6.17020500e-01 -6.85895862e-01 -3.39039647e-01 4.18948370e-02
-3.32480573e-01 -7.11635540e-01 -5.02358978e-02 -5.83572367e-01
-3.51788764e-01 7.87628070e-01 5.98624174e-02 1.05090455e+00
-1.34045888e-01 -2.58255106e-01 -7.76591443e-02 9.96015705e-01
2.93332068e-01 8.01433464e-01 -4.76398472e-01 -4.68813370e-01
-1.69022778e-01 -3.16089011e-02 -6.32884603e-01 -5.67476560e-01
6.90942449e-02 -7.15496815e-01 -3.75844753e-01 -1.74872224e-01
5.27170751e-01 -7.09236051e-01 -4.89251039e-01 -3.69361300e-01
-4.08684287e-01 -5.12796434e-01 -6.24368454e-01 -5.59603493e-01
-6.86695268e-01 -4.41151161e-01 -2.41920942e-01 -6.49945335e-01
-1.69932652e-01 2.99139771e-01 -4.98468347e-01 1.47801247e-02
-5.01090888e-01 -2.18205021e-02 -6.05519433e-01 -7.14213676e-01]
Unique values in p10r_30: [-1.65099223e-01 -4.79141390e-01 -4.31183812e-01 -5.28877467e-01
-4.05356666e-01 -5.99537489e-01 -2.36761736e-02 -5.53792899e-01
-1.67286460e-01 -2.31597906e-01 -2.80429765e-02 -2.96939962e-01
-6.02330161e-01 8.72669027e-01 9.04387248e-01 1.40746815e+00
-5.77275012e-01 -6.91398799e-01 -1.03949737e-01 -5.25439911e-01
5.97182388e-01 -6.68797230e-01 1.48848156e-01 5.18470355e-01
-5.57686860e-01 -1.37048678e-01 2.58248349e-01 -3.63895598e-01
-6.52630306e-01 2.42233086e-01 -6.54836939e-01 -9.60049388e-03
-5.10050903e-01 -4.74089706e-01 -5.81674142e-01 -3.30173688e-01
7.29978126e-01 -2.91792394e-01 3.98698495e-02 3.23291779e+00
-2.59234783e-01 2.82920512e-01 -3.17076019e-01 2.06806078e+00
-5.54527092e-01 -5.22363972e-01 -6.56840507e-02 3.22073804e-01
-2.68542593e-01 -5.36801817e-01 -4.76571167e-01 -6.45186414e-01
-5.55260737e-01 -5.89148114e-01 1.63285453e-01 -2.28353761e-01
-5.70596598e-01 -4.57009315e-01 -2.18610366e-01 -9.88432619e-02
-5.30571589e-01 -6.85949999e-01 1.09118998e+00 2.59661944e-01
-5.22984201e-01 -6.53170924e-01 -6.59960398e-01 -5.71387225e-01
-5.14526739e-01 1.77339216e-01 -2.00430330e-01 -3.63513708e-01
-6.25596399e-01 2.78723559e-01 -5.14368942e-01 3.60838258e-02
-5.47751151e-01 1.05663361e+00 -4.46139427e-01 -4.62175511e-01
-6.01394887e-01 -5.85649192e-01 -5.57612345e-01 2.33724296e-02
-8.68660584e-02 9.04579190e-02 1.45643442e+00 1.61625301e-01
3.05357222e-01 -4.85462570e-01 1.02338126e+00 -2.69257061e-01
3.24846203e-01 -5.70175807e-01 -2.23100447e-01 -3.63031552e-01
3.57358886e-01 5.76563062e+00 6.79992752e-01 -4.85592423e-01
8.95155224e-02 8.82553234e-01 -5.84247651e-01 -5.91910651e-01
-4.22406374e-01 -5.59927792e-01 4.33282084e-01 -8.20609314e-02
-4.49394531e-01 6.27722614e-01 6.49408694e-01 4.63526440e-01
-3.49762388e-01 -6.78715570e-01 -5.83997259e-01 -5.84607077e-01
-4.25966661e-01 -2.77530427e-01 -2.49270582e-01 2.51815944e-01
-4.85311896e-01 7.24515513e-01 8.23237037e-01 2.39170279e+00
-6.35411021e-01 -3.10947154e-01 2.19938831e-01 -5.29591935e-01
1.43155598e-02 1.43708242e+00 -5.82605580e-01 -5.85684258e-01
-2.55240555e-01 -2.69141170e-03 2.30108123e-02 8.02013124e-03
1.90021556e+00 1.18003278e+00 -4.90764099e-01 -5.52309173e-01
-2.06645764e-01 -5.90209406e-01 -8.26745850e-02 9.63210330e-01
-6.63351109e-01 -6.58751994e-01 3.22704070e-02 5.71067574e+00
2.81879492e-01 -5.90869084e-01 5.43202787e-01 1.27885293e+00
-6.38737298e-01 1.21129076e+00 -4.18180383e-01 1.16669695e-01
-1.27674024e-01 6.88835938e-01 -7.56776629e-03 -3.76047035e-01
3.87729261e-01 5.74756636e-01 -1.06524715e-02 -3.28293826e-01
9.18857420e-01 1.32846025e+00 1.43589346e+00 9.51034220e+00
2.17572960e+00 2.55859483e-01 -4.53001938e-01 8.02865929e-01
-2.73551541e-01 -2.96492871e-01 -4.31027111e-01 -4.31825409e-01
-6.65552207e-01 1.64981201e+00 -3.53403765e-01 -6.84893243e-02
-4.80319385e-01 8.52971842e-01 -5.51781540e-01 -7.63517612e-02
-6.29373656e-01 -6.67458807e-01 7.74506541e-02 -4.73205935e-01
-6.60565943e-01 -2.17000621e-01 -5.92336373e-01 1.55812029e-01
-3.28620925e-01 -5.79701136e-01 1.25023037e+00 3.79740981e-02
-6.75713599e-01 -3.46369760e-01 -5.57866573e-01 -6.18818266e-01
-5.22036325e-01 2.84623931e+00 -5.84623514e-01 -5.92290897e-01
1.53767777e+00 -4.95014746e-01 -3.80365887e-03 -5.70373053e-01
-5.37423141e-01 -6.89640457e-01 -2.67833056e-01 -3.18276479e-01
-3.50766698e-01 -6.21961049e-01 1.33759930e+00 -4.56046646e-01
-4.18304757e-01 -3.87617693e-01 -3.55694556e-01 1.31101688e-02
-4.73812466e-01 -2.63582957e-01 -1.36517210e-01 -5.25562467e-02
-1.66832247e-01 -2.32681662e-01 -6.81729541e-01 -4.17186856e-02
-6.02079220e-01 -6.56962974e-01 -3.72247314e-01 4.06259584e-02
-3.18755348e-01 -6.82578191e-01 -8.73591729e-02 -5.54455317e-01
-3.24311105e-01 7.67361684e-01 1.60962511e-02 1.17949583e+00
-1.49802811e-01 -2.29827625e-01 -1.11784778e-01 9.68798961e-01
2.71041931e-01 6.89685191e-01 -4.70414359e-01 -4.52422254e-01
-1.67685335e-01 -3.02126804e-02 -6.01966352e-01 -5.38699760e-01
2.53339296e-02 -6.86393692e-01 -3.65161258e-01 -1.64280105e-01
4.33950528e-01 -6.80162533e-01 -4.55529971e-01 -3.41308214e-01
-4.21874906e-01 -4.83673112e-01 -5.95439707e-01 -5.52025906e-01
-6.57505565e-01 -4.12482170e-01 -2.36800264e-01 -6.21012078e-01
-1.70165701e-01 2.27971118e-01 -4.80424035e-01 1.94165554e-02
-4.72795554e-01 -3.01304946e-02 -5.95116991e-01 -6.85131319e-01]
Unique values in p90_75: [-3.59237149e-01 -8.38378737e-01 -5.57529383e-01 -9.05592828e-01
-6.75981346e-01 -4.12211987e-01 2.82956581e+00 -7.77321285e-01
-1.95378928e-02 1.16082761e-01 -4.14725045e-01 -6.72247308e-01
-9.59679377e-02 4.89806850e-01 8.64907137e-01 1.45090718e+00
-9.10072336e-01 -9.74054530e-01 -4.68379183e-01 -9.55828328e-01
-1.09297000e-01 -6.42492562e-01 8.89661109e-01 1.60573830e+00
1.86212562e-01 -5.71506068e-01 4.14714287e-01 -6.96056948e-01
-9.23347899e-01 2.06704191e-01 -8.77447284e-01 1.85899310e-01
-8.42360561e-01 -6.59172016e-01 -8.34903044e-01 -2.23947346e-01
1.07842203e+00 -4.14718006e-01 5.08453265e-02 3.79251751e+00
-5.46452922e-01 -6.52790820e-01 -7.89088661e-01 -1.65738731e-01
-8.70494139e-01 1.78406334e+00 -4.51576188e-01 -1.31108512e-01
-7.24289077e-01 -7.44217907e-01 -2.15292431e-01 -8.70665899e-01
-6.42533742e-01 -9.29334890e-01 3.69774898e-01 -5.75212300e-01
-7.76167531e-01 -7.04874473e-01 -5.90445514e-01 2.57774877e-01
-4.14760242e-01 -8.34998428e-01 1.68946114e+00 1.95986124e+00
-6.37239074e-01 -9.23694940e-01 -9.56981061e-01 1.00159426e+00
-7.67524935e-01 -4.22683062e-01 -2.09211306e-02 1.33887970e-02
-8.78922738e-01 1.66664210e-01 7.25446503e-01 -4.36043801e-01
-8.60498926e-01 3.57192011e-01 -6.90499007e-01 -8.19953517e-01
-8.67075465e-01 -6.89746146e-01 -3.15360707e-01 -1.13298886e-01
-3.83589877e-01 -4.28476469e-01 1.05211235e+00 6.02961329e-01
4.93143515e-01 -7.79290199e-01 7.95516470e-01 -5.56983832e-01
-1.18705128e-01 -8.87649454e-01 -1.57981337e-01 -7.06566035e-01
6.01606248e-01 6.14958278e+00 1.40062401e-01 -7.59910088e-01
2.37297327e-01 4.74523463e-02 -8.52959400e-01 2.58484958e-02
2.97403749e-03 -8.90574668e-01 1.12788773e+00 6.20503458e-01
-7.40653166e-01 3.54048928e-01 3.54010212e-01 -3.53060095e-01
5.76468630e-01 -9.33464893e-01 -1.94681133e-01 -1.90651089e-01
-7.74421414e-01 -3.05727318e-01 4.31765509e+00 8.65807281e-02
1.53782149e-01 4.05541977e-01 -3.38601213e-01 1.19039389e+00
-8.77627140e-01 2.08100541e+00 -2.22581707e-01 -7.48099772e-01
-5.17468284e-01 1.30801485e+00 1.16726864e-01 -8.81715611e-01
1.54415078e+00 -4.15897101e-01 -1.10799907e-01 4.33449591e-01
3.26623512e-01 1.80941214e+00 -6.24332727e-01 -8.56297121e-01
-3.69813814e-01 -5.47258931e-01 4.19047024e-01 8.61373369e-01
5.18904118e-01 5.52080706e-01 1.51104459e+00 6.12248118e+00
1.63063568e-01 -7.25998941e-01 -1.12422483e-01 1.61217581e+00
-8.43829679e-01 2.25631408e+00 -7.53266675e-01 -3.98520397e-01
-3.37320046e-01 4.63682822e-02 -3.25185056e-02 -1.47985420e-01
-2.81990536e-01 2.06032724e+00 -1.08512109e-01 -1.85885430e-01
1.04752882e-01 8.69222276e-01 1.29989493e+00 2.68649046e+00
1.36117272e+00 7.24456574e-02 -6.90904475e-01 1.63369781e-01
-3.94046872e-01 -5.28717210e-01 -3.92206075e-01 -3.92251831e-01
-1.86913180e-01 1.33874526e+00 -6.35472894e-01 6.07913531e-01
-7.34463089e-01 4.96159888e-01 -8.86610794e-01 -2.48856185e-01
-9.23126511e-01 1.36810209e-01 -4.96174166e-01 -6.27229783e-01
-7.02565205e-01 -4.85410957e-01 -8.82360770e-01 5.24018226e-01
-5.33405436e-01 -2.37864196e-01 1.11392513e+00 6.15906744e-01
4.75316290e-01 -4.05323956e-01 -7.43286598e-01 -9.14635261e-01
-1.74576670e-01 2.70197709e+00 -7.53177275e-01 -5.55871610e-01
7.90450741e-02 -5.82861481e-02 -8.96500961e-02 -6.40551806e-01
-7.12217951e-01 -9.56983771e-01 -6.84323713e-01 -5.78689753e-01
5.60978479e-01 1.04554109e+00 5.38973384e-01 -2.92422894e-01
-6.98750566e-01 3.48220323e-01 -6.70720467e-01 -3.80094826e-01
-7.06715622e-01 -4.18895876e-01 -2.96787309e-01 -6.42505937e-01
8.99290978e-01 1.16100359e-01 6.27736419e-01 -4.53455702e-01
-8.55624861e-01 -9.08056963e-01 -7.54397552e-01 1.72915178e-01
-5.78957250e-01 -7.27597232e-01 5.35108766e-01 -4.44181321e-01
-4.94382644e-01 3.60771534e-01 5.79780657e-01 1.14986467e+00
-6.25840562e-01 -2.04729845e-01 1.81362169e+00 1.13896771e+00
1.02328962e+00 3.90213732e-01 -3.29354990e-01 -4.77495177e-01
-6.32388591e-01 -4.41527476e-01 -8.15981549e-01 -4.33206931e-01
-9.27579814e-02 -1.52416709e-01 -7.59580293e-01 -1.03394481e-01
1.11809596e+00 9.02096170e-01 -7.19683916e-01 -5.81164094e-01
7.35340349e-01 -6.97478550e-01 -7.94323143e-01 -8.28036131e-01
-3.35215272e-01 -7.20893281e-01 -2.43330273e-01 -9.24255627e-01
9.79927051e-01 2.76615772e-01 -8.67717104e-01 -2.93271139e-01
-5.16806583e-01 1.71954302e-01 -3.79503518e-01 1.15917425e+00]
Unique values in p00_75: [-0.31924652 -0.79259252 -0.52348636 -0.8416188 -0.63993105 -0.37849752
2.48655609 -0.75489318 -0.04907872 0.02972477 -0.46838691 -0.64485657
-0.17678918 0.37875966 0.7843808 1.29744527 -0.84935955 -0.90702928
-0.44340199 -0.85813168 -0.13885001 -0.59645468 0.74774372 1.34392068
0.16532951 -0.5518234 0.35160358 -0.6470247 -0.8592972 0.16317047
-0.80468163 0.14063226 -0.77100362 -0.63543825 -0.77901206 -0.1997271
0.86013195 -0.32344045 0.02215147 3.86143831 -0.54872867 -0.58669812
-0.74204552 -0.00895023 -0.82367332 1.82277359 -0.43665839 -0.16798344
-0.68471798 -0.70961539 -0.22709817 -0.80607214 -0.55163566 -0.86672424
0.31751314 -0.5433235 -0.69438037 -0.6382877 -0.56809948 0.32521059
-0.40517818 -0.77715643 1.55280866 1.70235481 -0.59382629 -0.85962635
-0.89218612 0.9409461 -0.72377179 -0.38496858 -0.07791236 0.02599414
-0.81498507 0.14232497 0.64043665 -0.38537738 -0.79517004 0.30936753
-0.65725546 -0.76848756 -0.80917535 -0.64919646 -0.11707186 -0.14411286
-0.38310933 -0.422611 1.07513671 0.46832201 0.38915515 -0.72664486
0.71703567 -0.52328954 -0.14417948 -0.82766316 -0.20127143 -0.68917384
0.52395441 6.84824307 0.11730977 -0.69246903 0.15063713 0.04806299
-0.79466798 -0.01479145 -0.0434101 -0.80862786 0.999864 0.52994098
-0.70929168 0.25808046 0.25804715 -0.35004541 0.50819311 -0.86959337
-0.2117608 -0.20821488 -0.75039916 -0.34122453 3.84984066 0.06499315
0.13877906 0.3365448 -0.24720178 1.50677536 -0.82721772 2.58487876
-0.25985624 -0.70355524 -0.52129401 1.19104361 0.02908887 -0.83772102
1.1588851 -0.45807923 -0.15356662 0.36332539 0.3436548 1.84961171
-0.62835278 -0.80305312 -0.3583606 -0.54057398 0.29187415 0.78046243
0.23984822 0.26569918 1.32636371 6.81656905 0.13922722 -0.68813732
-0.12059355 1.64773077 -0.78038591 2.21154331 -0.71332179 -0.3774074
-0.23995551 -0.14875798 -0.07254353 -0.18924076 -0.29249622 1.80182514
-0.14000978 -0.16161533 0.07590342 0.75460238 1.18344609 3.22608066
1.24471077 0.05180271 -0.65764245 0.19586495 -0.39565781 -0.48710364
-0.41049251 -0.25365467 1.21854792 -0.56941368 0.4880138 -0.70470107
0.38361674 -0.82982583 -0.25889936 -0.86403982 0.10880987 -0.5035705
-0.59161274 -0.53132311 -0.47692617 -0.8233157 0.46167229 -0.51937722
-0.26433178 1.00861221 0.69068508 0.38434954 -0.40478452 -0.69914601
-0.85522833 -0.15351817 2.65837095 -0.71613127 -0.54107361 0.14784521
-0.05890493 -0.16678431 -0.60793515 -0.67391732 -0.89111347 -0.66021362
-0.55327386 0.49451212 0.99206965 0.55390846 -0.33112276 -0.66785596
0.28243251 -0.63523324 -0.39684482 -0.63148566 -0.31991271 -0.31913146
-0.62540794 0.64024285 0.02974294 0.51318343 -0.44565187 -0.80870054
-0.83640894 -0.73287368 0.11956874 -0.55352217 -0.64391513 0.46140884
-0.31366572 -0.49322042 0.62942039 0.46056703 1.45136098 -0.58956271
-0.22776738 1.60717834 1.02154829 0.85859973 0.32192509 -0.34197853
-0.47082151 -0.60756602 -0.4182051 -0.76215579 -0.35960212 -0.12576253
-0.01549397 -0.72694313 -0.1162906 0.99084024 1.20039441 -0.67607758
-0.55992359 0.41510604 -0.63073075 -0.71849199 -0.7830031 -0.3351774
-0.65140849 -0.26335673 -0.86080943 0.70637068 0.2223397 -0.81432797
-0.11796212 -0.50757668 0.02960667 -0.40807002 1.23983552]
Unique values in p10_75: [-3.20529146e-01 -7.70555538e-01 -4.93460213e-01 -8.22734955e-01
-6.11820581e-01 -3.53213165e-01 2.26435858e+00 -7.55585320e-01
-7.02122157e-02 6.34829534e-02 -5.07691775e-01 -6.33040348e-01
-2.42336511e-01 3.55707340e-01 7.42603159e-01 1.13613181e+00
-8.30907914e-01 -8.89271182e-01 -4.36120808e-01 -8.41448985e-01
-1.70271431e-01 -5.89184078e-01 7.11019029e-01 1.29120503e+00
2.04112450e-01 -5.42064710e-01 2.74161996e-01 -6.24810999e-01
-8.40921931e-01 1.01387259e-01 -7.85075752e-01 1.34646347e-01
-7.48450556e-01 -6.13379688e-01 -7.59314893e-01 -1.69383703e-01
8.24101045e-01 -2.94997199e-01 9.68329380e-03 3.80643683e+00
-5.73316640e-01 -5.73830294e-01 -7.29615929e-01 1.39305523e-01
-8.17873110e-01 1.84650395e+00 -4.29504723e-01 -1.73512475e-01
-6.71968890e-01 -6.89097014e-01 -1.82797327e-01 -7.86677849e-01
-5.27372534e-01 -8.48319105e-01 3.07951488e-01 -5.33826707e-01
-6.73266983e-01 -6.15826802e-01 -5.57960064e-01 3.67510212e-01
-3.78047213e-01 -7.57665339e-01 1.47560677e+00 1.63244986e+00
-5.70547375e-01 -8.41255806e-01 -8.74870153e-01 9.95382278e-01
-7.02710516e-01 -3.94897293e-01 -8.53063813e-02 6.20508641e-02
-7.95922781e-01 9.11393061e-02 6.88147474e-01 -3.70881183e-01
-7.75660532e-01 2.78706716e-01 -6.36349786e-01 -7.55288852e-01
-7.94556853e-01 -6.26260117e-01 -8.43767795e-02 -1.84137294e-01
-4.05055915e-01 -4.41578380e-01 1.06328229e+00 4.44407547e-01
3.08618680e-01 -7.05932298e-01 6.86240813e-01 -5.14185030e-01
-1.88941633e-01 -8.08532146e-01 -2.02818662e-01 -6.89299963e-01
4.24771452e-01 6.81887719e+00 5.19787817e-02 -6.71210693e-01
1.85888904e-01 5.13311312e-02 -7.74777829e-01 -6.50477610e-02
-5.30438934e-02 -7.89436505e-01 8.62186805e-01 5.02634679e-01
-7.06679888e-01 2.38929249e-01 2.38895750e-01 -3.40787766e-01
5.52735473e-01 -8.51333472e-01 -2.15459014e-01 -2.12025349e-01
-7.53738120e-01 -3.66406253e-01 3.96081215e+00 5.40935861e-03
1.97228371e-01 2.59587068e-01 -1.81404320e-01 1.70108407e+00
-8.19033576e-01 3.14700576e+00 -2.91301124e-01 -6.82004682e-01
-5.58588173e-01 1.04388069e+00 8.44953049e-02 -8.28184153e-01
1.10104702e+00 -4.97055790e-01 -2.00867336e-01 2.76504146e-01
4.52709756e-01 1.87336470e+00 -6.43585327e-01 -7.83681628e-01
-3.25738266e-01 -5.16449015e-01 2.72794114e-01 7.37871402e-01
1.22636896e-01 1.45606157e-01 1.38625333e+00 6.78761131e+00
8.86938670e-02 -6.80454508e-01 -1.18688300e-01 1.67116373e+00
-7.62242441e-01 2.46027287e+00 -6.92023445e-01 -3.71690746e-01
-2.09945609e-01 -1.82554459e-01 -1.18110439e-01 -1.59278122e-01
-3.20219279e-01 1.72592649e+00 -1.80385388e-01 -1.29232162e-01
7.09588505e-02 6.38247676e-01 1.03673421e+00 3.54567374e+00
1.08749382e+00 -6.67825691e-03 -6.36735585e-01 1.96840339e-01
-3.89587676e-01 -4.61876083e-01 -4.49020778e-01 -4.49023570e-01
-3.12134814e-01 1.06330742e+00 -5.45732869e-01 3.99607996e-01
-7.02344538e-01 3.60433514e-01 -8.15603541e-01 -2.90377106e-01
-8.47628185e-01 1.44361105e-01 -5.27285995e-01 -5.68495552e-01
-5.06117314e-01 -4.68958365e-01 -8.03948065e-01 5.04354303e-01
-5.10421957e-01 -2.34109674e-01 8.73132657e-01 7.40788621e-01
4.24991989e-01 -3.78147711e-01 -6.77500719e-01 -8.36435835e-01
-1.20927161e-01 2.62210175e+00 -6.95196932e-01 -5.18391967e-01
2.42653240e-01 -2.75426538e-02 -2.09512912e-01 -5.99546486e-01
-6.51976309e-01 -8.73078534e-01 -6.78164840e-01 -5.43407468e-01
5.38791445e-01 1.04443064e+00 5.49603301e-01 -2.90952175e-01
-6.46653292e-01 3.22051845e-01 -6.26218522e-01 -4.17640435e-01
-6.09082582e-01 -2.91518869e-01 -3.45938263e-01 -6.29038314e-01
6.01775459e-01 6.34997030e-02 5.57676600e-01 -4.42734101e-01
-8.02795693e-01 -8.17428129e-01 -7.40747702e-01 1.14234189e-01
-5.43647546e-01 -6.21556275e-01 3.80449265e-01 -2.84698997e-01
-4.68882992e-01 6.46209311e-01 3.74134672e-01 1.64560387e+00
-5.88676007e-01 -1.98516811e-01 1.42018240e+00 1.00964455e+00
8.07633414e-01 2.46084113e-01 -3.66247132e-01 -4.66847917e-01
-5.99306409e-01 -4.11579878e-01 -7.38657633e-01 -3.31477790e-01
-1.67181133e-01 2.06989360e-02 -7.15803665e-01 -1.30373925e-01
8.53892970e-01 1.25591925e+00 -6.49390732e-01 -5.36716010e-01
2.76093782e-01 -6.08136231e-01 -6.97557507e-01 -7.80392289e-01
-3.06194295e-01 -6.29359069e-01 -2.66017629e-01 -8.42263294e-01
6.65496455e-01 1.47521193e-01 -7.99453314e-01 -1.12510495e-01
-4.84192110e-01 1.28433817e-02 -4.61524342e-01 1.30043126e+00]
Unique values in p90u_75: [-2.62215368e-01 -8.23518126e-01 -5.12601028e-01 -8.19942943e-01
-6.48863465e-01 -3.52985128e-01 3.18449309e+00 -7.11555779e-01
2.83991858e-02 2.13896712e-01 -5.55541950e-01 -6.89529245e-01
7.06965757e-02 3.13684871e-01 5.88174511e-01 1.15582110e+00
-8.26616151e-01 -8.63100159e-01 -4.59169149e-01 -8.46574393e-01
-3.68825293e-01 -4.93851138e-01 1.00531513e+00 1.82316230e+00
4.23911104e-01 -6.04042388e-01 4.60061989e-01 -6.53336054e-01
-8.25670623e-01 2.31209435e-01 -7.69651029e-01 1.79816357e-01
-7.78379798e-01 -5.87159229e-01 -7.63532999e-01 -8.98162834e-02
9.61886880e-01 -3.65815092e-01 -2.24976158e-02 2.97553227e+00
-5.64087260e-01 -7.80035408e-01 -7.78252068e-01 -7.25414500e-01
-8.59746483e-01 1.90360381e+00 -5.11009689e-01 -2.49267437e-01
-7.55404643e-01 -6.64808987e-01 -1.73642242e-01 -7.57316121e-01
-5.32504151e-01 -8.47694798e-01 4.03502756e-01 -5.94037945e-01
-6.95847005e-01 -6.33083097e-01 -6.23288554e-01 4.42985201e-01
-2.98520831e-01 -7.08002522e-01 1.49960231e+00 2.09428376e+00
-5.44717431e-01 -8.53730251e-01 1.36965520e+00 -6.88306046e-01
-5.46927488e-01 7.96864999e-02 1.92833442e-01 -7.94228505e-01
1.47190432e-02 1.02750926e+00 -6.34284737e-01 -7.85548550e-01
7.86898794e-02 -6.06694619e-01 -7.51581281e-01 -7.89970291e-01
-5.79934747e-01 -1.24083759e-01 -1.95185517e-01 -5.60782547e-01
-5.98783892e-01 1.02475126e+00 6.90663714e-01 4.60586740e-01
-6.93169554e-01 5.61855592e-01 -5.68031029e-01 -3.57541107e-01
-8.03613823e-01 -1.43410062e-01 -7.43745810e-01 5.88231460e-01
6.47223040e+00 -1.19515576e-01 -7.01100620e-01 3.60725361e-01
-5.27892848e-01 -7.59317091e-01 3.07707359e-02 1.49868926e-01
-8.05597302e-01 8.64824173e-01 7.97952968e-01 -7.21261643e-01
2.55404941e-01 2.53366954e-01 -5.81520797e-01 7.78451748e-01
-8.21264990e-01 -1.09449530e-02 -6.39710901e-03 -7.57958432e-01
-3.40118553e-01 5.07663620e+00 -4.35934288e-02 3.49323208e-01
1.08604767e-01 -6.61201221e-01 5.23951468e-01 -8.05912966e-01
2.61324239e+00 -2.18160672e-01 -6.53237612e-01 -6.99549553e-01
8.54516269e-01 3.62051476e-01 -7.82371975e-01 1.85252803e+00
-5.62466226e-01 -2.35518141e-01 4.45238784e-01 -4.08865032e-01
1.91948466e+00 -6.27978773e-01 -7.86358050e-01 -5.09954899e-01
-4.29395415e-01 5.37139403e-01 5.75844891e-01 8.00914355e-01
8.38578476e-01 1.76736375e+00 6.43740970e+00 9.18271436e-03
-6.21431586e-01 -1.98028936e-01 1.68238659e+00 -7.27960967e-01
2.14151544e+00 -6.83946542e-01 -4.62424641e-01 -3.07404992e-01
-1.00229951e-01 -1.40058163e-01 -3.46563865e-02 -5.45132757e-01
2.13523877e+00 -2.02723223e-01 -3.80937105e-02 -4.88938230e-02
6.03941455e-01 8.44033448e-01 1.16699767e-01 9.68008977e-01
-6.03285185e-02 -6.06996452e-01 -1.50943700e-01 -4.08934185e-01
-4.70275163e-01 -3.06990072e-01 -3.68042055e-02 9.31845889e-01
-5.87847507e-01 4.53244291e-01 -7.40758796e-01 3.24033453e-01
-8.10235859e-01 -3.10110104e-01 -8.36035558e-01 3.81084895e-01
-6.97666550e-01 -5.42621273e-01 -5.53314402e-01 -4.36221249e-01
-7.97333080e-01 6.43021184e-01 -5.39525241e-01 -6.92289502e-02
6.07403186e-01 8.36507946e-01 8.03485229e-01 -3.24697375e-01
-6.46238895e-01 -8.12788834e-01 6.97202205e-04 1.72750299e+00
-6.67679661e-01 -4.51833615e-01 -4.39007719e-01 1.30697201e-01
-1.59209549e-01 -5.32396353e-01 -6.18743151e-01 -8.63100274e-01
-7.76212046e-01 -5.97592422e-01 7.61464452e-01 1.45003976e+00
1.73161372e-01 -1.89116301e-01 -6.67126435e-01 5.62124070e-01
-6.28461219e-01 -5.34034065e-01 -6.44990069e-01 -3.67531720e-01
-2.52830863e-01 -6.55182853e-01 1.10214190e+00 2.13807220e-01
9.36084577e-01 -5.12911811e-01 -8.10392877e-01 -8.03708197e-01
-7.94357049e-01 1.77387857e-01 -5.97980087e-01 -5.82926236e-01
5.72680112e-01 -3.01246283e-01 -4.79259799e-01 -1.10350735e-01
4.17634428e-01 1.07938234e+00 -7.10858959e-01 -2.26556691e-01
2.07987141e+00 9.09135143e-01 1.08247390e+00 9.32120646e-02
-2.21211551e-01 -3.68837496e-01 -5.98086665e-01 -4.77249473e-01
-7.33505025e-01 -2.77071116e-01 -1.73532410e-01 8.71428488e-02
-7.64605688e-01 -1.07718843e-01 8.53552191e-01 1.28144411e+00
-6.52110821e-01 -5.65060287e-01 1.06025943e+00 -6.27822568e-01
-7.01860492e-01 -7.94867156e-01 -1.67422516e-01 -6.58923638e-01
-2.50101344e-01 -8.37330961e-01 1.19498219e+00 1.54575416e-01
-7.87960779e-01 -5.08113795e-01 -4.55974675e-01 1.73433918e-01
-3.12933185e-01 1.56375213e+00]
Unique values in p00u_75: [-2.31281453e-01 -7.74645478e-01 -4.84143837e-01 -7.67564219e-01
-6.14034468e-01 -3.25598048e-01 2.82923493e+00 -6.91129889e-01
-1.20483769e-03 1.23573450e-01 -5.66872995e-01 -6.57556060e-01
-2.57082441e-02 2.34265631e-01 5.36815321e-01 1.03911046e+00
-7.75868108e-01 -8.09023423e-01 -4.34847400e-01 -7.63406119e-01
-3.65573948e-01 -4.60700857e-01 8.63258126e-01 1.55109972e+00
3.92380687e-01 -5.78620237e-01 3.99457254e-01 -6.11792614e-01
-7.73603289e-01 1.90448065e-01 -7.09758616e-01 1.37567838e-01
-7.21189776e-01 -5.68960688e-01 -7.16500757e-01 -7.72585289e-02
7.74508241e-01 -2.84987162e-01 -3.93463336e-02 3.05370250e+00
-5.54956071e-01 -7.26398779e-01 -7.32783563e-01 -6.55406985e-01
-8.06256918e-01 1.93233476e+00 -4.89238894e-01 -2.67147582e-01
-7.11376420e-01 -6.37235095e-01 -1.90455377e-01 -7.04934486e-01
-4.52013189e-01 -7.95148049e-01 3.51226535e-01 -5.61424462e-01
-6.27882456e-01 -5.77664583e-01 -5.94533693e-01 5.11429990e-01
-2.97852685e-01 -6.63105485e-01 1.39132664e+00 1.84129540e+00
-5.09657929e-01 -8.00848566e-01 1.29914431e+00 -6.52711469e-01
-5.04593915e-01 1.78659102e-02 1.96804981e-01 -7.42386316e-01
3.72688736e-03 9.26873146e-01 -5.85241731e-01 -7.33731104e-01
5.80746385e-02 -5.81622310e-01 -7.08275924e-01 -7.40230539e-01
-5.50132999e-01 8.41937317e-02 -2.11501637e-01 -5.34688727e-01
-5.68720099e-01 1.05355639e+00 5.56820910e-01 3.72957169e-01
-6.51012175e-01 5.09436839e-01 -5.30030046e-01 -3.52062856e-01
-7.53894733e-01 -1.81957147e-01 -7.11003894e-01 5.20136354e-01
7.24577462e+00 -1.20144782e-01 -6.45357977e-01 2.67934003e-01
-4.92601851e-01 -7.11816324e-01 -3.45198279e-03 9.40465987e-02
-7.41006986e-01 7.70109199e-01 7.00278371e-01 -6.88103475e-01
1.80704557e-01 1.78912485e-01 -5.54602948e-01 6.99728050e-01
-7.70229397e-01 -4.29869203e-02 -3.89547588e-02 -7.26638309e-01
-3.62585986e-01 4.57435300e+00 -4.90475094e-02 3.26250417e-01
7.55826152e-02 -6.02332733e-01 7.50029529e-01 -7.61145216e-01
3.19678603e+00 -2.49170421e-01 -6.18279350e-01 -6.68406207e-01
7.83856647e-01 2.50824656e-01 -7.47767823e-01 1.43692570e+00
-5.62798148e-01 -2.57513432e-01 3.83998871e-01 -3.69542611e-01
1.94927478e+00 -6.14749180e-01 -7.40840478e-01 -4.86347944e-01
-4.33266990e-01 4.04579475e-01 5.24944610e-01 4.80506169e-01
5.10085936e-01 1.57604056e+00 7.20510024e+00 -1.22600389e-03
-5.94045107e-01 -1.96568881e-01 1.70414900e+00 -6.76676548e-01
2.11536949e+00 -6.50345440e-01 -4.37345011e-01 -2.21640248e-01
-2.50158177e-01 -1.62254940e-01 -8.37001097e-02 -5.24102098e-01
1.88587848e+00 -2.18359486e-01 -2.24239551e-02 -6.17754522e-02
5.23942743e-01 7.74021419e-01 3.05990834e-01 8.92481595e-01
-6.47140266e-02 -5.81911582e-01 -1.14345242e-01 -4.06202473e-01
-4.33979585e-01 -3.30843739e-01 -1.17513117e-01 8.54198991e-01
-5.35145211e-01 3.61375729e-01 -7.04945069e-01 2.42876747e-01
-7.61914960e-01 -3.10185526e-01 -7.86047429e-01 3.37722498e-01
-6.71866881e-01 -5.15032733e-01 -3.77374106e-01 -4.30222584e-01
-7.48538626e-01 5.79609854e-01 -5.21984772e-01 -1.10514160e-01
5.51360030e-01 9.16311211e-01 6.87783256e-01 -3.30275779e-01
-6.11848352e-01 -7.64733240e-01 1.24826396e-02 1.72037642e+00
-6.38747067e-01 -4.46785137e-01 -3.56722948e-01 1.17583415e-01
-2.10517408e-01 -5.10971292e-01 -5.89966733e-01 -8.09023517e-01
-7.34284953e-01 -5.68898248e-01 6.84601271e-01 1.38325526e+00
1.97320026e-01 -2.36749388e-01 -6.37488384e-01 4.81003574e-01
-5.97255667e-01 -5.25692033e-01 -5.82859475e-01 -2.80252988e-01
-2.74167705e-01 -6.31197436e-01 8.23539748e-01 1.23499369e-01
7.99660744e-01 -4.96572983e-01 -7.65045088e-01 -7.45152739e-01
-7.54024200e-01 1.27009430e-01 -5.69251371e-01 -5.07673598e-01
5.03203393e-01 -1.74566615e-01 -4.75643137e-01 5.25749537e-02
3.27301672e-01 1.35942565e+00 -6.69601745e-01 -2.43674264e-01
1.86567887e+00 8.20008520e-01 9.23941627e-01 6.09461866e-02
-2.40389975e-01 -3.71250018e-01 -5.74419099e-01 -4.51999079e-01
-6.87650165e-01 -2.10686738e-01 -1.91996982e-01 2.30057085e-01
-7.27439803e-01 -1.18310378e-01 7.59691900e-01 1.62117748e+00
-6.14942145e-01 -5.44348276e-01 6.91370928e-01 -5.72220636e-01
-6.38729428e-01 -7.50024493e-01 -1.81286884e-01 -6.01286065e-01
-2.63189502e-01 -7.84908581e-01 9.00334256e-01 1.19001551e-01
-7.42789885e-01 -3.91312050e-01 -4.50778494e-01 4.73645403e-02
-3.44072615e-01 1.65827478e+00]
Unique values in p10u_75: [-0.23503958 -0.75847082 -0.45888469 -0.75199427 -0.59165514 -0.30382469
2.58415156 -0.6904119 -0.02384187 0.15433729 -0.58385303 -0.6461011
-0.09992794 0.21611088 0.50738172 0.90374409 -0.76060029 -0.79409454
-0.4283605 -0.74953276 -0.37903594 -0.45763588 0.82317989 1.49221761
0.43085662 -0.56889696 0.32197965 -0.59351599 -0.75829911 0.13018071
-0.69308838 0.13098723 -0.70307947 -0.550307 -0.70019746 -0.04933181
0.74120752 -0.26045472 -0.04940661 3.00965598 -0.56978836 -0.71275414
-0.72035104 -0.6181903 -0.79171654 1.95343005 -0.48157522 -0.27000287
-0.69868556 -0.61998741 -0.15145417 -0.68842715 -0.43056868 -0.78005128
0.34036376 -0.5521672 -0.61016185 -0.55879042 -0.58445044 0.55294686
-0.27341107 -0.64634143 1.32185324 1.76702959 -0.48951034 -0.7861968
1.35586692 -0.63503129 -0.50704565 0.00758965 0.23145753 -0.72661392
-0.03565024 0.97532926 -0.57231491 -0.71767196 0.04119357 -0.56391052
-0.69716228 -0.72753329 -0.53009131 0.11592677 -0.24177142 -0.54057314
-0.57203588 1.04055332 0.53030576 0.2982491 -0.63359418 0.48682196
-0.5214339 -0.37459032 -0.73805838 -0.18449223 -0.70410388 0.42639474
7.20834128 -0.16122022 -0.62784838 0.30050931 -0.48251443 -0.69508256
-0.04998873 0.08030329 -0.72512707 0.65636355 0.66788573 -0.68247581
0.16429521 0.16255859 -0.54360085 0.74317179 -0.75484571 -0.05173186
-0.04782934 -0.72267856 -0.38158233 4.69541315 -0.09511158 0.38520043
0.02308589 -0.57238939 0.879568 -0.7518463 3.83604643 -0.27682252
-0.59986115 -0.67346978 0.67286795 0.3082428 -0.74005387 1.36961029
-0.57840837 -0.2912033 0.30060362 -0.32259254 1.97038649 -0.62235624
-0.72489779 -0.46265712 -0.41181708 0.38209793 0.49570019 0.34386627
0.37015297 1.63585299 7.16827544 -0.03994951 -0.58905574 -0.19396233
1.72488241 -0.6614445 2.3475062 -0.63256132 -0.43092315 -0.19594611
-0.28073805 -0.19633962 -0.05658073 -0.52983017 1.80767755 -0.24813577
0.00796364 -0.06422642 0.43112655 0.66365476 0.40229995 0.76903572
-0.10950862 -0.56419833 -0.11003871 -0.40046726 -0.41237319 -0.36961787
-0.18299951 0.73377323 -0.51542337 0.28735132 -0.69793595 0.22447202
-0.74914641 -0.33311307 -0.77187265 0.37263757 -0.67124599 -0.49521061
-0.35399479 -0.42398318 -0.73247063 0.61970917 -0.51362757 -0.08207067
0.45639534 0.96647705 0.72909671 -0.3068654 -0.593302 -0.74900039
0.04359362 1.69693063 -0.62104694 -0.42695885 -0.30874836 0.14744935
-0.24439911 -0.50537049 -0.57118091 -0.79409462 -0.73006147 -0.55935661
0.7277601 1.43799214 0.19698529 -0.19968603 -0.62017603 0.51957384
-0.58915785 -0.53218664 -0.56420646 -0.25578145 -0.29971078 -0.62979801
0.77903917 0.15425924 0.84481609 -0.49172762 -0.75550946 -0.72920194
-0.74716295 0.12080166 -0.55970166 -0.48759128 0.42365323 -0.14772401
-0.45554478 0.07602028 0.25580923 1.53693395 -0.66186239 -0.21924739
1.66272832 0.80977149 0.87046538 0.00956692 -0.26756705 -0.37017072
-0.56688066 -0.44525189 -0.66801471 -0.18441092 -0.22374829 0.26632326
-0.7155207 -0.1261431 0.64678938 1.67949289 -0.59262329 -0.52536504
0.5284358 -0.55325047 -0.62100271 -0.74207082 -0.15411764 -0.58294374
-0.26554425 -0.76963231 0.85304064 0.05780528 -0.72994277 -0.38294171
-0.43090689 0.0306893 -0.395407 1.72235553]
Unique values in p90r_75: [-4.83204053e-01 -4.59376589e-01 -4.16169867e-01 -7.16183652e-01
-4.18183130e-01 -3.89840610e-01 2.71278293e-01 -5.90205228e-01
-1.60890493e-01 -2.51759855e-01 2.41147492e-01 -2.76023140e-01
-5.73721159e-01 7.97939285e-01 1.30054783e+00 1.64696783e+00
-7.11455442e-01 -8.29852827e-01 -2.59404082e-01 -8.15507689e-01
7.66660436e-01 -7.85765270e-01 7.26055355e-02 1.03435707e-01
-6.59333669e-01 -1.78223063e-01 6.10440605e-02 -4.77375105e-01
-7.62933639e-01 2.45302148e-02 -7.72321793e-01 1.10961658e-01
-6.16575624e-01 -5.51796396e-01 -6.36259572e-01 -5.33903300e-01
8.99335208e-01 -3.58446056e-01 2.57053038e-01 4.44889960e+00
-2.12993624e-01 8.10815508e-02 -4.22398639e-01 1.68746449e+00
-4.62185643e-01 5.00552384e-01 -3.41937990e-02 3.09127886e-01
-2.57917919e-01 -6.17030730e-01 -2.37363614e-01 -7.86535350e-01
-6.63756162e-01 -7.15196819e-01 7.56459991e-02 -2.23383910e-01
-6.35637338e-01 -5.73591312e-01 -1.86576946e-01 -4.58225970e-01
-5.71269504e-01 -8.12107255e-01 1.43182129e+00 5.40046269e-01
-6.05817654e-01 -7.64201249e-01 -7.97102793e-01 -6.70006789e-01
-6.27901833e-01 1.84859706e-01 -3.28010567e-01 -5.60290409e-01
-7.00036027e-01 5.62480133e-01 -5.97340354e-01 4.12141104e-01
-6.60174457e-01 1.05623084e+00 -6.04481907e-01 -6.19427103e-01
-6.70220200e-01 -6.86304445e-01 -7.59504151e-01 2.03267045e-01
3.71443889e-01 3.27582792e-01 6.04558091e-01 1.98403159e-02
3.45858999e-01 -6.55505128e-01 1.13026902e+00 -2.38996337e-01
6.96633355e-01 -7.02249844e-01 -1.23574427e-01 -2.30029219e-01
3.38610740e-01 2.00734954e+00 8.89551729e-01 -5.59651462e-01
-2.73052099e-01 1.84193032e+00 -7.15536991e-01 -2.59483374e-03
-4.62543042e-01 -7.06665266e-01 1.38677358e+00 -2.55165432e-01
-4.25595947e-01 4.86256420e-01 4.92543044e-01 5.48492715e-01
-3.54374535e-01 -8.13811586e-01 -6.76265130e-01 -6.75920587e-01
-4.32961196e-01 -4.15551919e-02 -2.73345218e-01 4.54257630e-01
-5.42057913e-01 1.13829121e+00 8.53130448e-01 2.69237304e+00
-6.58375891e-01 -6.57581385e-01 -1.23286451e-01 -6.67780116e-01
3.20995335e-01 2.07728663e+00 -7.17643974e-01 -7.47709081e-01
-2.14335799e-01 2.58748755e-01 3.39853923e-01 1.76321982e-01
2.48545439e+00 5.42938888e-01 -2.95534816e-01 -6.42265934e-01
2.61125845e-01 -6.41621844e-01 -1.66729725e-01 1.32659426e+00
-6.35636052e-01 -6.33481373e-01 -6.60987391e-02 2.01843148e+00
5.66838345e-01 -6.87574626e-01 2.15448183e-01 5.71852217e-01
-7.81288268e-01 1.47360356e+00 -5.89600992e-01 6.05088178e-03
-2.60334862e-01 4.86372124e-01 3.24107793e-01 -4.30757664e-01
6.93085076e-01 7.77575250e-01 2.44576209e-01 -5.58332428e-01
5.37385060e-01 1.26646636e+00 2.08075777e+00 9.44411762e+00
1.91278020e+00 4.55517526e-01 -6.05010292e-01 1.07399795e+00
-1.46663952e-01 -4.44698800e-01 -4.62127791e-01 -4.62287206e-01
-5.66166925e-01 1.94513896e+00 -4.63057286e-01 7.88271511e-01
-3.41366751e-01 7.88438640e-01 -6.77527597e-01 7.13302122e-02
-7.29367693e-01 -7.04434092e-01 3.92826125e-01 -5.75882266e-01
-8.17258044e-01 -3.94138398e-01 -7.02782086e-01 -1.17943463e-01
-2.42961152e-01 -6.49803455e-01 2.14933211e+00 -3.93801569e-01
-8.02970694e-01 -4.54076026e-01 -6.72319598e-01 -7.71821306e-01
-6.39634294e-01 4.40993282e+00 -6.40683350e-01 -6.02170384e-01
1.67639541e+00 -6.25708585e-01 1.75953012e-01 -6.56858873e-01
-6.45734505e-01 -8.33073340e-01 -4.61795248e-02 -2.24852075e-01
-3.57272296e-01 -7.63545589e-01 1.42163927e+00 -4.70193697e-01
-4.43631745e-01 -5.04394734e-01 -4.63446825e-01 2.99673522e-01
-5.42685290e-01 -3.68274531e-01 -2.84761419e-01 -2.75938290e-01
-1.98228413e-01 -2.51424312e-01 -6.65306605e-01 -3.50512998e-02
-5.63851544e-01 -7.76492692e-01 -2.44786716e-01 7.12029369e-02
-2.24602667e-01 -8.15105679e-01 1.44873432e-01 -6.70123779e-01
-2.90893771e-01 1.66675334e+00 7.98042134e-01 7.88952883e-01
-3.91061082e-02 -3.15544453e-02 5.14328532e-02 1.28721607e+00
3.16844106e-01 1.13095039e+00 -5.03646510e-01 -5.78191219e-01
-4.19431455e-01 -1.04187455e-01 -6.62047588e-01 -7.06439384e-01
2.09871215e-01 -8.31881710e-01 -3.57745400e-01 -3.69887114e-02
1.38664502e+00 -7.54647765e-01 -5.67548954e-01 -3.36706421e-01
-6.64707512e-01 -5.63203598e-01 -6.82946436e-01 -5.12148237e-01
-6.95053009e-01 -5.50434936e-01 -9.81219552e-02 -7.29397648e-01
-1.97109934e-01 5.22086322e-01 -6.78916054e-01 5.34890980e-01
-4.46394517e-01 8.01996235e-02 -3.96947452e-01 -7.07853425e-01]
Unique values in p00r_75: [-4.25583187e-01 -4.50040981e-01 -3.80398377e-01 -6.44406692e-01
-3.97852819e-01 -3.49017336e-01 2.04775089e-01 -5.69925719e-01
-1.69253245e-01 -2.69081717e-01 6.44228766e-02 -2.83455837e-01
-5.45527737e-01 6.26901937e-01 1.14156339e+00 1.43046634e+00
-6.46568364e-01 -7.49597229e-01 -2.47186229e-01 -7.15239556e-01
6.17299964e-01 -7.08746956e-01 2.39952616e-02 4.42512579e-02
-6.04643418e-01 -1.94304888e-01 3.09590948e-02 -4.29661088e-01
-6.88477609e-01 -8.69467962e-04 -6.89137892e-01 7.97401054e-02
-5.35739920e-01 -5.18474527e-01 -5.78184056e-01 -4.70351449e-01
6.89106483e-01 -2.77779032e-01 1.97473745e-01 4.37467247e+00
-2.55030154e-01 1.30111476e-01 -3.98496866e-01 1.95299948e+00
-4.63960103e-01 5.79009562e-01 -5.87120063e-02 2.16536705e-01
-2.61106419e-01 -5.73399091e-01 -2.24161788e-01 -7.08649014e-01
-5.76971794e-01 -6.49443295e-01 5.67391625e-02 -2.16384084e-01
-5.47978964e-01 -5.02172535e-01 -2.03525558e-01 -4.01147822e-01
-5.27132323e-01 -7.33302158e-01 1.26478692e+00 4.29895950e-01
-5.51254742e-01 -6.89638711e-01 -7.21993299e-01 -6.14267820e-01
-5.76474072e-01 1.70102249e-01 -3.28701528e-01 -5.03959420e-01
-6.26694844e-01 4.90936298e-01 -5.47118097e-01 4.12828150e-01
-5.83008540e-01 9.15591273e-01 -5.57092827e-01 -5.65965306e-01
-6.12729795e-01 -6.24006506e-01 -6.67636202e-01 1.32250825e-01
2.67776418e-01 2.31477972e-01 6.02603285e-01 -3.38002816e-02
2.43650795e-01 -5.91752850e-01 9.86927840e-01 -2.40775657e-01
5.57594707e-01 -6.36569175e-01 -1.58807496e-01 -2.77949923e-01
2.73502355e-01 2.21748630e+00 7.77745826e-01 -4.88327110e-01
-2.79684473e-01 1.66117001e+00 -6.47589121e-01 -4.15000168e-02
-4.37637454e-01 -6.08446824e-01 1.19528744e+00 -2.50792042e-01
-4.18244460e-01 3.63397752e-01 3.68706072e-01 4.44699436e-01
-3.25831617e-01 -7.35008404e-01 -6.16557767e-01 -6.16259775e-01
-4.46567609e-01 -1.05557669e-01 -2.70270482e-01 3.77955581e-01
-4.98066864e-01 9.58431664e-01 9.51948463e-01 3.04405698e+00
-6.13045945e-01 -5.61209179e-01 -1.61951901e-01 -6.09415566e-01
1.85228293e-01 1.82799227e+00 -6.56605255e-01 -6.90595704e-01
-2.62708528e-01 8.84481011e-02 2.38221782e-01 1.19106056e-01
2.33120398e+00 6.22383990e-01 -3.54850081e-01 -5.89288806e-01
2.08710937e-01 -5.94705003e-01 -1.95226634e-01 1.16370453e+00
-6.08608103e-01 -6.06984633e-01 -9.31819125e-02 2.22887195e+00
4.95005654e-01 -6.28405896e-01 1.70007191e-01 6.52471594e-01
-7.03604614e-01 1.39615985e+00 -5.46778450e-01 -6.83572136e-03
-1.75096671e-01 2.32918802e-01 2.35595392e-01 -4.13856818e-01
5.55330393e-01 6.45764098e-01 1.67491880e-01 -5.01948240e-01
4.54974294e-01 1.07552446e+00 1.83097219e+00 1.04527210e+01
1.68839518e+00 3.78874123e-01 -5.57582004e-01 1.03727678e+00
-1.65497902e-01 -4.03946173e-01 -4.45981237e-01 -4.45980169e-01
-5.38687800e-01 1.71203163e+00 -3.87979556e-01 6.27403931e-01
-3.51060559e-01 6.17951488e-01 -6.19914719e-01 2.61719935e-02
-6.67528754e-01 -6.38509863e-01 2.58217169e-01 -5.27173978e-01
-7.31293434e-01 -3.79433907e-01 -6.37451403e-01 -1.26248371e-01
-2.51328214e-01 -5.97543939e-01 1.88845586e+00 -3.37898701e-01
-7.26503983e-01 -4.27584755e-01 -6.13334324e-01 -7.00981107e-01
-5.79065216e-01 4.16802179e+00 -5.91804117e-01 -5.55545190e-01
1.60173178e+00 -5.63552530e-01 4.93085816e-02 -5.97037673e-01
-5.90598263e-01 -7.52214733e-01 -1.05314149e-01 -2.28858104e-01
-3.28294592e-01 -6.88617954e-01 1.35653435e+00 -4.50923209e-01
-4.25338598e-01 -4.59907835e-01 -4.32084545e-01 1.92091728e-01
-4.62451984e-01 -2.79660976e-01 -2.95337077e-01 -2.94663123e-01
-2.34934368e-01 -2.68785861e-01 -6.10809401e-01 -6.82285329e-02
-5.35924696e-01 -6.93884726e-01 -3.01837366e-01 3.74155935e-02
-2.28655170e-01 -7.33931787e-01 1.04162653e-01 -5.77610501e-01
-2.99377595e-01 2.06112047e+00 6.33758962e-01 1.00355773e+00
-5.19543111e-02 -6.53970726e-02 2.03776998e-02 1.12070393e+00
2.31268630e-01 9.51168770e-01 -4.78197510e-01 -5.36449120e-01
-4.03636432e-01 -1.06371541e-01 -6.06078907e-01 -6.30291045e-01
1.37926563e-01 -7.50969766e-01 -3.61406978e-01 -5.17620581e-02
1.19499906e+00 -6.74159349e-01 -5.22600491e-01 -3.26641216e-01
-6.28869440e-01 -4.92000212e-01 -6.00184215e-01 -4.90762316e-01
-6.33147071e-01 -4.76933980e-01 -1.31844004e-01 -6.59582294e-01
-2.34201671e-01 4.24149720e-01 -6.23155252e-01 7.68891505e-01
-4.25298011e-01 -3.87550703e-02 -3.97391411e-01 -6.47354145e-01]
Unique values in p10r_75: [-4.08117194e-01 -4.10572197e-01 -3.42042294e-01 -6.09075221e-01
-3.57145649e-01 -3.17492263e-01 1.58811919e-01 -5.59955965e-01
-1.70810150e-01 -2.37008856e-01 -2.21768947e-02 -2.69419119e-01
-5.38032730e-01 5.85331748e-01 1.05588999e+00 1.23911307e+00
-6.11775916e-01 -7.13579767e-01 -2.34997251e-01 -6.80676565e-01
5.33400468e-01 -6.74828705e-01 1.53477981e-02 3.55799792e-02
-5.69573473e-01 -1.84494057e-01 -7.43056091e-03 -3.96313409e-01
-6.52994630e-01 -3.54097258e-02 -6.53444362e-01 7.65616387e-02
-4.98044397e-01 -4.84527484e-01 -5.43899592e-01 -4.36532078e-01
6.46025412e-01 -2.45332641e-01 1.79304188e-01 4.20465694e+00
-2.89299077e-01 1.30844271e-01 -3.82320467e-01 2.30349797e+00
-4.75135514e-01 5.83565835e-01 -5.52109857e-02 2.00500903e-01
-2.48070766e-01 -5.39204567e-01 -1.81283742e-01 -6.72708074e-01
-5.42207579e-01 -6.14231879e-01 5.44714100e-02 -2.05543932e-01
-5.13778298e-01 -4.67905827e-01 -1.93241085e-01 -3.68123102e-01
-4.92626691e-01 -6.97163955e-01 1.17230589e+00 3.97741875e-01
-5.16688216e-01 -6.54141994e-01 -6.87377053e-01 -5.79062376e-01
-5.41610624e-01 1.38934840e-01 -3.15467221e-01 -4.69521062e-01
-5.91797105e-01 4.18750482e-01 -5.12300306e-01 4.14114960e-01
-5.48525517e-01 8.36820801e-01 -5.23352618e-01 -5.39015499e-01
-5.84387948e-01 -5.88470662e-01 -6.31994277e-01 8.06539503e-02
2.02954946e-01 1.70240447e-01 5.84909464e-01 -3.69376245e-02
1.81054745e-01 -5.56928000e-01 9.22793895e-01 -2.28709065e-01
4.56103382e-01 -6.01374304e-01 -1.52602051e-01 -2.91663865e-01
2.02202514e-01 2.17034429e+00 6.54691822e-01 -4.54513680e-01
-2.47562106e-01 1.60064538e+00 -6.12155011e-01 -7.59000008e-02
-4.19135915e-01 -5.73885564e-01 1.02734746e+00 -2.42781664e-01
-4.15243229e-01 3.36769888e-01 3.41779706e-01 4.32839397e-01
-2.92716695e-01 -6.98979582e-01 -5.87858351e-01 -5.87577149e-01
-4.58382373e-01 -1.33381431e-01 -2.39499369e-01 2.99493766e-01
-4.58505219e-01 8.24526591e-01 1.06574648e+00 3.25272423e+00
-5.96787729e-01 -5.01227839e-01 -1.84326103e-01 -5.74215713e-01
6.73107496e-02 1.60329425e+00 -6.18961455e-01 -6.63047666e-01
-2.56348483e-01 -1.68654479e-03 1.69022543e-01 6.36963862e-02
2.50861261e+00 6.25880567e-01 -3.75747240e-01 -5.54777233e-01
2.45710197e-01 -5.59987636e-01 -1.89562419e-01 1.07409617e+00
-5.92961264e-01 -5.91570607e-01 -6.15423599e-02 2.18106453e+00
4.23030902e-01 -6.00774469e-01 1.64570331e-01 6.55229274e-01
-6.68329378e-01 1.53066148e+00 -5.12158265e-01 -5.93529322e-03
-1.43314692e-01 2.01092100e-01 1.73575528e-01 -3.80401956e-01
4.62907906e-01 5.99161535e-01 1.12334814e-01 -4.67576638e-01
4.33712756e-01 9.22150872e-01 1.60592393e+00 1.10028368e+01
1.46943036e+00 3.00415112e-01 -5.23829607e-01 1.00166495e+00
-1.57342184e-01 -3.70733582e-01 -4.52706498e-01 -4.52714176e-01
-5.32835763e-01 1.49035259e+00 -3.54910425e-01 5.26039298e-01
-3.54711760e-01 5.76914869e-01 -5.92962224e-01 -1.50287857e-02
-6.35993302e-01 -6.03177647e-01 1.68362245e-01 -4.92815759e-01
-6.95100140e-01 -3.60816637e-01 -6.02104663e-01 -9.46801023e-02
-2.38814118e-01 -5.62439760e-01 1.65511036e+00 -3.05194214e-01
-6.90347050e-01 -3.94240380e-01 -5.78089205e-01 -6.65013684e-01
-5.44184634e-01 4.00695145e+00 -5.57048927e-01 -5.21976358e-01
1.74558461e+00 -5.29622569e-01 1.17634579e-03 -5.69585950e-01
-5.55619881e-01 -7.15819866e-01 -1.76777784e-01 -2.17258462e-01
-2.95166899e-01 -6.52797692e-01 1.30838677e+00 -4.10768942e-01
-3.92728797e-01 -4.25926043e-01 -4.14013808e-01 1.34939461e-01
-4.28735188e-01 -2.47176292e-01 -3.04617413e-01 -3.03773806e-01
-2.29966318e-01 -2.36716137e-01 -5.75684108e-01 -7.07347051e-02
-5.30152343e-01 -6.58093320e-01 -3.41465493e-01 3.64341436e-02
-2.17065555e-01 -6.97720793e-01 5.79206988e-02 -5.42621225e-01
-2.67415192e-01 1.99749595e+00 5.31538581e-01 1.12201576e+00
-7.03892004e-02 -3.52494500e-02 -2.42048155e-02 1.08157251e+00
2.07955168e-01 8.18000391e-01 -4.69309920e-01 -5.12357890e-01
-3.87239111e-01 -1.00780180e-01 -5.67856506e-01 -5.95172494e-01
8.57635813e-02 -7.14581088e-01 -3.49089630e-01 -7.57445237e-02
1.02708834e+00 -6.38410875e-01 -4.83451621e-01 -2.94568024e-01
-6.10076225e-01 -4.57819009e-01 -5.65294973e-01 -4.92788886e-01
-5.97647652e-01 -4.43149454e-01 -1.30685534e-01 -6.24160245e-01
-2.29282027e-01 3.36779485e-01 -5.94111027e-01 7.43515330e-01
-3.92751831e-01 -4.61952318e-02 -4.19595629e-01 -6.11875728e-01]
Unique values in p90_150: [-8.45634320e-01 -9.43483513e-01 3.40336120e-01 -9.60188643e-01
-4.34125962e-01 3.67224274e-01 2.11055694e+00 -9.29971424e-01
-7.16668510e-01 -2.33244601e-01 -1.65665395e-01 -4.12294141e-01
-6.72691780e-01 9.78569190e-01 3.47782251e-01 1.11297478e+00
-1.08428257e+00 -1.15101641e+00 -7.94352173e-01 -1.13447465e+00
6.28710124e-02 -7.60270002e-01 1.38273578e+00 1.17724603e+00
3.03308351e-02 -9.02464127e-01 -1.51948098e-01 -8.39500350e-01
-1.00125024e+00 -1.67990699e-01 -1.01687305e+00 -2.66842480e-01
-1.03872140e+00 6.96487502e-02 -7.89610102e-01 -1.05792642e-01
8.60545088e-01 -5.94401872e-01 -6.67936789e-02 2.80171031e+00
-6.12409782e-01 -7.40076330e-01 -2.42698255e-01 1.71912853e-01
-4.14872730e-01 1.24777108e-02 -5.67302647e-01 8.05666518e-01
-6.65823750e-01 -8.95307634e-01 -5.87049551e-01 -1.07097874e+00
-5.82638158e-01 -9.53141203e-01 -2.70790689e-01 -3.18289966e-01
-6.32245805e-01 -6.83645214e-01 4.55205878e-01 -1.42188390e-01
-6.70866037e-04 -1.06422281e+00 2.55306817e+00 1.79553285e+00
1.15369165e-01 -1.00249439e+00 -1.11377206e+00 3.27464302e-02
-9.49896566e-01 -1.47161467e-01 1.10932793e+00 -7.25364652e-01
-8.85766033e-01 1.33329816e+00 -5.59211555e-02 -1.75760472e-01
-9.78913023e-01 4.38484331e-01 -8.03422381e-01 -7.97336489e-01
-8.64506450e-01 -9.64298673e-01 -8.68465212e-01 2.19636920e+00
-2.88364729e-01 -2.54700011e-01 6.18211645e-01 1.70834044e-01
-4.01165757e-03 -5.55080439e-01 2.31552256e-01 -6.17332437e-01
6.75974857e-01 -9.97847302e-01 2.70412849e-01 -7.79459912e-01
4.75632901e-01 3.03444000e+00 6.42226882e-01 -7.32908110e-01
1.06995139e+00 5.89271408e-01 -9.84844130e-01 6.87912118e-01
8.91494042e-02 -1.02142633e+00 8.69410087e-01 5.94946884e-01
-8.52639546e-01 -6.59411848e-02 -6.18510898e-02 1.19778212e-01
6.24508609e-01 -1.12925966e+00 -5.76450248e-01 -5.76499498e-01
-8.26267345e-01 -3.66608884e-02 1.65649541e+00 4.03098228e-02
-4.35481509e-01 3.00367048e+00 -9.11560112e-02 8.88781753e-01
-9.94517064e-01 -4.70338761e-02 -1.98960739e-01 -9.04950080e-01
-5.86419854e-01 1.03512460e+00 -7.25277879e-01 -1.10797909e+00
3.68760405e-01 -3.81772041e-01 -3.85156220e-01 7.94401188e-02
1.90041543e-01 3.57014301e-02 -7.14825153e-01 -9.89602618e-01
-5.71159391e-01 2.42683949e-02 -7.87004522e-02 3.96774273e-01
-4.91938424e-01 -4.92960947e-01 1.28594781e+00 3.01995816e+00
1.32445662e+00 -8.24459166e-01 -8.64947355e-01 -3.14427339e-02
-6.31135335e-01 1.06146163e+00 -9.86680451e-01 -4.51348217e-01
-6.19847704e-01 -5.31352494e-01 2.32672925e+00 3.92107249e-01
2.95451804e-02 2.56883990e+00 2.24409479e+00 -7.30311932e-01
5.54635990e-03 1.97433379e+00 1.03697734e+00 4.59588774e+00
1.06588240e+00 3.98642276e-02 -8.02796203e-01 3.27038621e-01
5.15982720e-01 -3.50237971e-01 -7.30351801e-01 -7.35899462e-01
1.10497752e+00 1.07783139e+00 -7.82514585e-01 2.38869044e+00
-8.36580529e-01 8.19714494e-01 -1.01879731e+00 -4.92654894e-01
-1.03697830e+00 1.68279726e+00 -2.19979935e-01 -9.17505290e-02
-9.02242502e-01 -3.79616768e-01 -1.06356709e+00 7.58609318e-01
3.77613678e-01 -4.42217033e-01 1.06251698e+00 -1.27006492e-01
-2.55439933e-01 -3.77429833e-01 -8.68207236e-01 -1.09865185e+00
-6.94759297e-01 3.74536372e+00 -8.40366916e-01 -6.38881656e-01
1.56012140e-01 -1.65372240e-01 -8.51264043e-02 -8.45474844e-01
-8.26195815e-01 -1.12218854e+00 -7.42328932e-01 3.95214690e-01
6.21975752e-01 9.70736095e-01 7.45206283e-01 -6.75813291e-01
-5.65629320e-01 -1.88722603e-01 1.64865413e-01 -4.61940484e-01
-7.89834072e-01 -6.82857214e-01 -6.41978543e-01 -4.33621736e-01
3.66086834e-01 -2.33212940e-01 1.44312566e+00 2.69697552e-01
-8.70659182e-01 -7.31666307e-01 -7.17652337e-01 -3.07299008e-01
3.98650463e-01 -7.93267501e-01 -1.23372316e-03 -8.15275214e-01
-1.35350849e-01 2.57713032e+00 2.27779586e+00 1.59197792e+00
-2.64369427e-01 5.25281589e-01 1.69413648e+00 2.01830701e+00
1.56861934e+00 2.96968798e+00 -7.09266939e-01 -4.41484146e-01
2.00278507e-01 -4.14720290e-01 -4.59266913e-01 -7.81492061e-01
2.20509349e+00 -6.91499416e-01 -6.31617281e-01 1.00746606e-01
8.67275921e-01 -1.33814718e-01 -4.67794198e-01 5.78052983e-02
-5.09637935e-01 -6.77419779e-01 -9.09496324e-01 -1.00317920e+00
-8.14316012e-01 -8.66273587e-01 7.47613690e-02 -8.75055331e-01
3.67634691e-01 6.29832299e-01 -2.77365563e-01 1.51462378e-01
-2.76533004e-01 -1.27807391e-01 -4.38531491e-01 1.91777019e-01]
Unique values in p00_150: [-8.03727628e-01 -9.13394157e-01 3.34257005e-01 -9.05568673e-01
-4.45128287e-01 3.65784657e-01 1.90822713e+00 -8.83483786e-01
-6.95958971e-01 -2.79402591e-01 -3.00221195e-01 -4.29951528e-01
-6.83917375e-01 8.37280946e-01 3.19212776e-01 1.02153910e+00
-1.03269293e+00 -1.09450101e+00 -7.64457324e-01 -1.07184623e+00
2.57105291e-02 -7.20679963e-01 1.22868975e+00 9.86884572e-01
6.68673158e-02 -8.66648331e-01 -1.66929117e-01 -7.89639065e-01
-9.48223670e-01 -1.80841664e-01 -9.50428018e-01 -2.74742297e-01
-9.75410964e-01 1.06305354e-01 -7.56151418e-01 -9.22991795e-02
6.86424498e-01 -5.10344451e-01 -9.57138985e-02 2.89225225e+00
-6.46279882e-01 -6.70511134e-01 -2.65151471e-01 4.01412456e-01
-4.66853894e-01 1.06802341e-01 -5.53230341e-01 6.80905865e-01
-6.53352637e-01 -8.67897012e-01 -5.63095545e-01 -1.01420095e+00
-4.67235953e-01 -9.09306434e-01 -2.77034652e-01 -3.13646073e-01
-5.22301145e-01 -6.06326219e-01 3.59147802e-01 -9.25632041e-02
-3.18468488e-02 -1.01084473e+00 2.34180740e+00 1.61120455e+00
1.68770484e-01 -9.49459927e-01 -1.06149802e+00 7.20960396e-02
-9.12479907e-01 -1.51468661e-01 9.19894783e-01 -6.81833133e-01
-8.33086136e-01 1.22477598e+00 -7.57940138e-02 -1.39843292e-01
-9.10156490e-01 3.96577181e-01 -7.78509649e-01 -7.68665152e-01
-8.21949472e-01 -9.20993926e-01 -7.50060214e-01 1.94275741e+00
-3.06541221e-01 -2.75412195e-01 6.87532366e-01 7.91884670e-02
-6.64299389e-02 -5.38321748e-01 2.07442333e-01 -5.96425812e-01
5.89429083e-01 -9.49734306e-01 1.80698187e-01 -7.77573655e-01
4.05636851e-01 3.70394691e+00 6.02319699e-01 -6.53890005e-01
9.33737959e-01 5.81736128e-01 -9.38998338e-01 5.97463716e-01
4.71741816e-02 -9.40000596e-01 7.84206811e-01 5.15605714e-01
-8.33976572e-01 -1.16981862e-01 -1.13276198e-01 8.13834956e-02
5.66619422e-01 -1.07370227e+00 -5.68589329e-01 -5.68694939e-01
-8.27269310e-01 -1.09186404e-01 1.48696800e+00 2.77398952e-02
-4.20307898e-01 2.75682312e+00 4.07754661e-02 1.23031532e+00
-9.62548303e-01 2.00142827e-01 -2.38177468e-01 -8.66217608e-01
-6.12254867e-01 9.57696903e-01 -7.20336213e-01 -1.06152691e+00
1.87076195e-01 -4.57769374e-01 -4.11061857e-01 3.60954994e-02
2.28015549e-01 1.31972693e-01 -7.49828286e-01 -9.46593965e-01
-5.30163903e-01 5.66480080e-02 -1.41259707e-01 3.65380854e-01
-5.74667073e-01 -5.75584429e-01 1.16665949e+00 3.68685261e+00
1.21691736e+00 -8.12894979e-01 -8.26491732e-01 5.80147239e-02
-5.82624052e-01 1.12199273e+00 -9.45404301e-01 -4.29489744e-01
-5.34643004e-01 -5.94156235e-01 2.05920782e+00 3.10670801e-01
-2.93619107e-02 2.33100828e+00 1.98537410e+00 -6.85935352e-01
-9.39957492e-03 1.79101053e+00 9.59384591e-01 5.87553428e+00
9.89649065e-01 2.73050310e-02 -7.77930865e-01 4.01723074e-01
4.13930332e-01 -3.30359352e-01 -7.17243501e-01 -7.22624427e-01
8.13021739e-01 9.95892472e-01 -7.00666893e-01 2.11173320e+00
-8.19789647e-01 6.93661880e-01 -9.74767986e-01 -4.96830530e-01
-9.92823235e-01 1.53124132e+00 -2.66439497e-01 -1.14392949e-02
-7.42100129e-01 -3.95372580e-01 -1.01298892e+00 6.81464976e-01
2.86618672e-01 -4.52049875e-01 9.81852572e-01 -7.62920368e-02
-2.74137628e-01 -3.85094254e-01 -8.28724034e-01 -1.04772732e+00
-6.56120237e-01 3.80110799e+00 -8.19234677e-01 -6.25797780e-01
2.68157653e-01 -1.56636896e-02 -1.79159154e-01 -8.13064783e-01
-7.95484882e-01 -1.06695008e+00 -7.38295068e-01 3.06964102e-01
5.64341562e-01 9.74925807e-01 8.06550546e-01 -6.79226019e-01
-5.71459432e-01 -2.10772743e-01 1.17477221e-01 -4.86855574e-01
-7.13395988e-01 -5.93245091e-01 -6.39265109e-01 -4.54689086e-01
1.92615536e-01 -2.79373600e-01 1.28950861e+00 1.78834483e-01
-8.55964133e-01 -6.30728311e-01 -7.42552595e-01 -3.15256106e-01
3.10080629e-01 -6.97729489e-01 -2.69080344e-02 -7.31723442e-01
-1.72921960e-01 3.20129571e+00 2.00809058e+00 2.04882285e+00
-3.26951881e-01 4.55884370e-01 1.53937949e+00 1.89799747e+00
1.39164992e+00 2.72541972e+00 -7.00050835e-01 -4.50315595e-01
1.52639095e-01 -3.97306690e-01 -4.42650597e-01 -7.00403904e-01
1.95066780e+00 -5.79304589e-01 -6.30685860e-01 7.56267225e-02
7.82063552e-01 1.01900201e-02 -4.74809837e-01 7.65331253e-03
-5.89944265e-01 -5.99639665e-01 -8.34730337e-01 -9.65060161e-01
-7.84712675e-01 -7.98582771e-01 5.11660493e-03 -8.34531542e-01
1.93650927e-01 5.41749333e-01 -2.82332747e-01 4.56298526e-01
-2.99223078e-01 -2.31560285e-01 -5.03900179e-01 2.36578232e-01]
Unique values in p10_150: [-7.98347031e-01 -8.93530649e-01 4.16806626e-01 -8.88775975e-01
-3.99436055e-01 4.19597793e-01 1.77796542e+00 -8.95201472e-01
-6.97921253e-01 -2.41943524e-01 -3.78195085e-01 -4.24608886e-01
-7.15449390e-01 8.15458838e-01 2.88471123e-01 8.98844933e-01
-1.02047280e+00 -1.08407956e+00 -7.56489227e-01 -1.06155596e+00
-1.73360409e-02 -7.17027174e-01 1.19964157e+00 9.63516645e-01
1.17618791e-01 -8.57880283e-01 -2.07340814e-01 -7.69062075e-01
-9.33229176e-01 -2.20235421e-01 -9.35232419e-01 -2.70223466e-01
-9.58921474e-01 1.58410524e-01 -7.34209323e-01 -4.81357863e-02
6.69601013e-01 -4.80486486e-01 -1.17254951e-01 2.90214644e+00
-6.85880471e-01 -6.60119363e-01 -2.68465419e-01 6.59647791e-01
-5.35549027e-01 1.38387782e-01 -5.46887171e-01 6.59405502e-01
-6.46252693e-01 -8.50763778e-01 -5.23449127e-01 -1.00120367e+00
-4.35480867e-01 -8.92440350e-01 -2.72500980e-01 -3.09144730e-01
-4.93383031e-01 -5.79616504e-01 3.58463496e-01 -4.82714680e-02
1.52372582e-02 -9.97820545e-01 2.22307892e+00 1.56703853e+00
2.23324525e-01 -9.34505553e-01 -1.05156736e+00 1.23084825e-01
-8.95997149e-01 -1.74264524e-01 8.99610566e-01 -6.57127581e-01
-8.14499937e-01 1.11925985e+00 -3.04777825e-02 -1.23986701e-01
-8.94082098e-01 3.62970067e-01 -7.59261010e-01 -7.62026978e-01
-8.16223094e-01 -9.04600338e-01 -7.27677218e-01 1.76580253e+00
-3.44713687e-01 -3.15514017e-01 6.98317075e-01 7.12253417e-02
-1.19400660e-01 -5.08438854e-01 1.89607623e-01 -5.89421445e-01
4.86188432e-01 -9.34467756e-01 1.72783093e-01 -7.88286233e-01
3.21519308e-01 3.74773416e+00 5.06065801e-01 -6.28873806e-01
1.01407746e+00 5.92117072e-01 -9.23218774e-01 5.02993579e-01
3.84679032e-02 -9.24744224e-01 6.68312037e-01 4.99301099e-01
-8.39716380e-01 -1.23160981e-01 -1.19517928e-01 9.17520443e-02
6.33083253e-01 -1.06259256e+00 -5.66533881e-01 -5.66643395e-01
-8.49355596e-01 -1.59716538e-01 1.58677052e+00 -2.72795710e-02
-3.72840503e-01 2.52945789e+00 1.52614977e-01 1.44872409e+00
-9.65986614e-01 4.34716611e-01 -2.80758181e-01 -8.47828208e-01
-6.64588136e-01 8.44485030e-01 -6.89162030e-01 -1.05459452e+00
1.68896781e-01 -5.20043516e-01 -4.42257198e-01 -2.01465903e-02
3.56893465e-01 1.64002548e-01 -7.78150810e-01 -9.31454653e-01
-4.96808994e-01 1.07016235e-01 -1.45715156e-01 3.31850500e-01
-6.16916372e-01 -6.17820593e-01 1.25417592e+00 3.73059950e+00
1.11212687e+00 -8.16142655e-01 -8.17354098e-01 8.87282808e-02
-5.63002280e-01 1.33163078e+00 -9.29870085e-01 -4.24080697e-01
-5.05623459e-01 -6.02495345e-01 1.87504568e+00 3.68542708e-01
-8.94605549e-02 2.22994054e+00 1.80578986e+00 -6.61366665e-01
-1.27228631e-02 1.62799838e+00 8.46035678e-01 6.50958358e+00
8.68006421e-01 -2.75606260e-02 -7.58664980e-01 4.12164374e-01
4.12813708e-01 -2.94438773e-01 -7.45748082e-01 -7.50599672e-01
6.27655985e-01 8.70380851e-01 -6.77266622e-01 1.92427875e+00
-8.26449618e-01 6.74165733e-01 -9.67977259e-01 -5.23170010e-01
-9.84101090e-01 1.63440449e+00 -3.29975748e-01 3.70044792e-02
-7.19363807e-01 -3.91838849e-01 -9.99840749e-01 7.51901654e-01
2.84323140e-01 -4.20157557e-01 8.65128031e-01 -3.14081712e-02
-2.36175113e-01 -3.51179890e-01 -8.08987383e-01 -1.03561526e+00
-6.30564012e-01 3.81123320e+00 -8.00120584e-01 -6.01833413e-01
4.00447290e-01 2.98036576e-02 -2.30999826e-01 -8.08919542e-01
-7.75022378e-01 -1.05561194e+00 -7.73154816e-01 3.06720312e-01
6.30728206e-01 1.05735992e+00 8.16835038e-01 -6.47054184e-01
-5.44428425e-01 -1.70730015e-01 1.07859400e-01 -5.13807004e-01
-6.90534353e-01 -5.66242165e-01 -6.56862033e-01 -4.83860115e-01
1.74459731e-01 -2.41913480e-01 1.38286032e+00 1.68295905e-01
-8.70828194e-01 -6.04124495e-01 -7.78593714e-01 -3.10662427e-01
3.09811916e-01 -6.73683656e-01 -7.69972218e-02 -7.08991910e-01
-1.32258439e-01 3.23035077e+00 1.82713065e+00 2.34512461e+00
-3.47512607e-01 5.18470984e-01 1.38460479e+00 1.90770620e+00
1.32175509e+00 2.49999558e+00 -7.13508172e-01 -4.50523121e-01
1.43756901e-01 -3.92142194e-01 -3.96421013e-01 -6.76507773e-01
1.77323594e+00 -5.50434278e-01 -6.30571765e-01 2.25446868e-02
6.66305886e-01 5.66783254e-02 -4.30540115e-01 5.38774675e-02
-6.31678540e-01 -5.72701583e-01 -8.15819926e-01 -9.68844652e-01
-7.63486526e-01 -7.78617943e-01 -2.85686537e-03 -8.15168654e-01
1.75467652e-01 4.41587919e-01 -2.62810400e-01 4.74296900e-01
-2.63562464e-01 -2.40529527e-01 -5.70601424e-01 2.93956540e-01]
Unique values in p90u_150: [-0.79090501 -1.00391685 0.4674096 -0.91817178 -0.33014982 0.63867743
2.24962462 -0.90032892 -0.69878474 -0.15542671 -0.34985475 -0.41951651
-0.59003377 1.05924774 0.04322729 0.70591347 -1.04047953 -1.08142043
-0.83515196 -1.07557891 -0.18340386 -0.6151912 1.58307338 1.42460283
0.28412095 -0.91621193 -0.19314561 -0.83058089 -0.93363348 -0.2015875
-0.96540998 -0.30451212 -1.03340753 0.31820053 -0.71328737 0.06524868
0.75424116 -0.57856654 -0.28416301 1.90977782 -0.70868035 -0.87706951
-0.098857 -0.77463809 -0.42787069 0.13724415 -0.69609732 0.84830834
-0.77246687 -0.85275756 -0.58301971 -0.99741166 -0.43980092 -0.89441198
-0.30627355 -0.32831506 -0.50622454 -0.64606427 0.62990627 0.04230129
0.18520518 -0.98021083 2.89930933 2.00125678 0.3657647 -0.93512314
-1.05450578 0.28599021 -0.91461299 -0.31036724 1.41862118 -0.647101
-0.80155263 1.4366524 0.1147727 -0.59240486 -0.93202304 0.14451703
-0.75845025 -0.77026832 -0.7980341 -0.90626744 -0.75372533 2.54489664
-0.51802392 -0.495193 0.51787976 0.24911824 -0.01967061 -0.41696137
-0.01692566 -0.67742623 0.32620961 -0.96391558 0.33391386 -0.89401656
0.34360816 2.92897314 0.37974106 -0.70932309 1.47714356 0.13149544
-0.92363291 0.86343501 0.2390242 -0.97144297 0.43948565 0.7948186
-0.87996256 -0.10735065 -0.10294925 -0.10935508 0.90434316 -1.06029001
-0.45422158 -0.45432942 -0.86096507 -0.14727384 2.16261751 -0.12736042
-0.35858853 3.47727178 -0.67894034 -0.022 -0.96668295 0.15293304
-0.31949069 -0.85019811 -0.86043737 0.61985537 -0.60157864 -1.04468653
0.52736988 -0.65068711 -0.54643243 0.00462553 -0.47270574 0.16369138
-0.8151767 -0.96982634 -0.76750325 0.27416783 -0.01631887 0.08938089
-0.32399274 -0.32505103 1.6574989 2.91137329 1.42726293 -0.75434506
-0.8463316 0.0796032 -0.50528559 0.37703781 -0.95361363 -0.44833196
-0.61709354 -0.69907807 2.69936985 0.68136858 -0.27387774 2.87738142
2.60275759 -0.65210775 -0.15764395 2.01093383 0.62143706 1.74640403
0.68739336 -0.12697362 -0.75786215 0.06172871 0.68020388 -0.22952583
-0.76956232 -0.7769114 1.50023617 0.68098034 -0.78534035 2.760236
-0.8676326 0.87354342 -0.98354099 -0.66735377 -1.00358556 2.29657194
-0.48222749 0.09773651 -0.78416991 -0.40418854 -1.01677049 1.01050305
0.47659776 -0.33254391 0.64547868 0.06015709 -0.06777543 -0.29707245
-0.8052926 -1.04192864 -0.61779954 3.40730374 -0.79595922 -0.56746023
-0.71276829 0.08136462 -0.21009985 -0.83287721 -0.76167258 -1.06255929
-0.93300368 0.51869936 0.90174057 1.49116305 0.22408159 -0.61436297
-0.55960644 -0.02658114 0.36980519 -0.54712838 -0.77450437 -0.67902661
-0.65535596 -0.48861894 0.52791628 -0.1553692 1.97162174 0.41991588
-0.90334851 -0.58898554 -0.84224654 -0.33992751 0.5229124 -0.65098332
-0.05306287 -0.75008457 -0.08326876 2.44753668 2.63219133 1.42635706
-0.42953146 0.72828713 1.77579463 1.33968067 1.68220196 3.43647866
-0.66106297 -0.29830185 0.37742604 -0.42212773 -0.35916081 -0.67079753
2.55501943 -0.51734954 -0.67132667 0.05925696 0.43727129 0.12874906
-0.33712649 0.19207833 -0.34354382 -0.64092092 -0.86343969 -1.02865931
-0.71979385 -0.85850627 0.11633857 -0.79323297 0.52969927 0.45665413
-0.14311976 -0.27348088 -0.22746101 -0.21942029 -0.42563907 0.48638983]
Unique values in p00u_150: [-0.7736289 -0.99117993 0.47079923 -0.89372018 -0.35619204 0.65221175
2.11173109 -0.87149567 -0.69655849 -0.20890926 -0.4523913 -0.44317931
-0.62381201 0.95203228 0.03792619 0.66995191 -1.02186725 -1.06116673
-0.82359329 -1.04416147 -0.20020093 -0.59963463 1.46877196 1.25495635
0.33640009 -0.90468647 -0.20674336 -0.80813082 -0.91167338 -0.21418923
-0.93241885 -0.31511219 -1.00855582 0.37452368 -0.7041819 0.07522786
0.62126839 -0.51513939 -0.30045585 2.05727446 -0.73835373 -0.84289969
-0.13236356 -0.70351385 -0.47925535 0.23400689 -0.68995032 0.7517881
-0.7696206 -0.85119903 -0.57578733 -0.97403497 -0.3276263 -0.87987128
-0.31604588 -0.3295555 -0.40445737 -0.58974801 0.54391656 0.09655945
0.1507557 -0.96031087 2.75780692 1.86929978 0.43985586 -0.91318701
-1.03650164 0.34210745 -0.90511781 -0.31139846 1.24534326 -0.62511786
-0.77618538 1.36835398 0.09142809 -0.56561008 -0.89494056 0.12983836
-0.75728534 -0.76531378 -0.78043302 -0.89221575 -0.64766719 2.34775806
-0.52537713 -0.50355897 0.60433042 0.16230719 -0.07257831 -0.42010132
-0.02261918 -0.66662115 0.28711165 -0.94590242 0.25383537 -0.89505102
0.30549618 3.67215499 0.37222233 -0.65430956 1.36047677 0.14972601
-0.90827526 0.79359385 0.19855551 -0.92575504 0.40641389 0.73153617
-0.8789468 -0.1509309 -0.14680029 -0.13275677 0.8636734 -1.04029637
-0.46687801 -0.46704107 -0.87316448 -0.20288103 2.03115737 -0.12823822
-0.34929192 3.31960055 -0.62345299 0.1975337 -0.96076049 0.43890902
-0.35044128 -0.83867703 -0.86568179 0.59237652 -0.62314396 -1.03184185
0.34598688 -0.69463588 -0.56395179 -0.02037174 -0.44060311 0.26383508
-0.84168852 -0.95522527 -0.74558919 0.32193443 -0.0804542 0.08309061
-0.44167751 -0.44264145 1.57435813 3.65060116 1.35974033 -0.76938389
-0.83285526 0.16795669 -0.47275632 0.44415611 -0.94132982 -0.43596884
-0.55432161 -0.7534927 2.49078399 0.60237098 -0.30629077 2.71209544
2.40132046 -0.62964956 -0.16290452 1.8925895 0.59387569 2.72379947
0.66016787 -0.12787921 -0.75672512 0.12855355 0.59103516 -0.22214402
-0.77021106 -0.77760827 1.20266957 0.65193559 -0.73440855 2.5446883
-0.86775301 0.77839176 -0.9692229 -0.6699088 -0.98939277 2.18067969
-0.51098643 0.19773096 -0.62532958 -0.42540233 -0.99899902 0.95654294
0.39715587 -0.35717702 0.61641582 0.11615253 -0.09944893 -0.31737409
-0.79120468 -1.02461875 -0.59869173 3.58657088 -0.79931465 -0.57400016
-0.65129807 0.26125757 -0.28357048 -0.82399833 -0.7566883 -1.04251291
-0.92674923 0.44046079 0.86124054 1.53587947 0.28871602 -0.63907854
-0.57830698 -0.05904371 0.32353881 -0.5741343 -0.72589354 -0.61488012
-0.66645809 -0.5122581 0.35127342 -0.20885534 1.84689116 0.32920672
-0.90350028 -0.49734926 -0.85757707 -0.35162089 0.44441912 -0.56689884
-0.07067541 -0.68754244 -0.12143804 3.11497722 2.42103321 1.90305737
-0.5015877 0.67668502 1.67481556 1.30588863 1.55488209 3.28060902
-0.67096743 -0.32446753 0.3353612 -0.413 -0.35026506 -0.60654001
2.3572528 -0.40671796 -0.68486367 0.04210939 0.40413883 0.30283976
-0.36232021 0.14088486 -0.45892321 -0.58401566 -0.81881831 -1.01296943
-0.7168091 -0.82192974 0.0522485 0.35258848 0.40897826 -0.15644626
-0.06853055 -0.25711936 -0.29959185 -0.49637875 0.55521293]
Unique values in p10u_150: [-0.77952739 -0.99148735 0.56790966 -0.89066426 -0.31168517 0.72525357
2.00140279 -0.89359516 -0.7078971 -0.17222914 -0.51533361 -0.44371707
-0.6673319 0.94376525 0.02004939 0.58090812 -1.02537209 -1.06637222
-0.82699928 -1.04924615 -0.23015855 -0.60692028 1.45862942 1.24722939
0.40206675 -0.90870713 -0.24439437 -0.80090486 -0.90996573 -0.25138729
-0.9314057 -0.31430611 -1.01023626 0.44208702 -0.6914278 0.12624309
0.61535405 -0.49359242 -0.31606965 2.09965368 -0.77504542 -0.84483342
-0.13892433 -0.64349221 -0.5500645 0.27190713 -0.69236394 0.74091422
-0.77263945 -0.84696567 -0.54657241 -0.97522677 -0.29624949 -0.87591725
-0.31529474 -0.3292081 -0.37807607 -0.57182943 0.55088667 0.14897791
0.20675233 -0.96097058 2.66054991 1.84880832 0.51101638 -0.91155054
-1.04177628 0.40811604 -0.90275283 -0.32972054 1.23929283 -0.60822513
-0.768045 1.27388875 0.14415098 -0.56118444 -0.89253904 0.10935759
-0.74919472 -0.76989103 -0.78631034 -0.88896446 -0.63209856 2.181544
-0.55593506 -0.53515251 0.62504041 0.15636203 -0.12444479 -0.39263185
-0.03160951 -0.66868049 0.21028941 -0.94546116 0.2493098 -0.90877212
0.23592388 3.77578064 0.29705416 -0.63962767 1.47752718 0.16304999
-0.90581622 0.70016903 0.19126666 -0.92468274 0.32346354 0.72367875
-0.89287275 -0.15783584 -0.15371258 -0.12372862 0.95387656 -1.04460782
-0.4726724 -0.47283738 -0.8988208 -0.2487826 2.18271887 -0.17561249
-0.30400732 3.10710965 -0.58229569 0.3263507 -0.97481544 0.72117905
-0.38941473 -0.83257612 -0.89359016 0.5100165 -0.59699521 -1.03969853
0.33067519 -0.73739237 -0.590306 -0.07003497 -0.37990711 0.30271599
-0.86821066 -0.95546023 -0.7329179 0.38683105 -0.08621806 0.06287558
-0.50118778 -0.50213267 1.70105078 3.75387073 1.26593968 -0.78459179
-0.83572825 0.2036402 -0.45834409 0.60018084 -0.94060086 -0.43640543
-0.53468757 -0.76991603 2.31777791 0.67978394 -0.35143047 2.63579033
2.23257547 -0.61296457 -0.16479377 1.75223223 0.51144133 3.12059555
0.56973444 -0.17513755 -0.74861104 0.14164127 0.59834356 -0.18597502
-0.80054866 -0.80730661 0.99719644 0.56013558 -0.72371274 2.36913434
-0.88222651 0.77029825 -0.97585082 -0.6935613 -0.99478196 2.34150011
-0.55824604 0.2569339 -0.6085126 -0.42749648 -1.00120457 1.05162751
0.40066692 -0.32768578 0.53218888 0.16956672 -0.05724023 -0.28612069
-0.78264952 -1.02800041 -0.58050716 3.65250771 -0.79223714 -0.55740488
-0.61300582 0.32000145 -0.33035421 -0.83071009 -0.74690125 -1.04689168
-0.94710659 0.44666148 0.95133935 1.66214287 0.30409083 -0.61555176
-0.56055826 -0.01483149 0.31633938 -0.60227333 -0.71493502 -0.59830755
-0.69026669 -0.54349903 0.33594956 -0.1721729 1.98934171 0.32223868
-0.92290545 -0.47397974 -0.88634977 -0.35129174 0.45064851 -0.54744231
-0.11566583 -0.67417109 -0.08070121 3.19611163 2.25143575 2.2179397
-0.52064923 0.75763724 1.53607027 1.33635636 1.49999953 3.06996404
-0.69403749 -0.33073917 0.32963781 -0.41326442 -0.3050572 -0.58902615
2.19059294 -0.37826855 -0.69283263 -0.00605003 0.32130129 0.36373378
-0.31809941 0.19392884 -0.51801579 -0.56581014 -0.81237726 -1.02264217
-0.70465374 -0.81574686 0.04523641 -0.77158708 0.33726191 0.3255008
-0.13680708 -0.0502848 -0.22397303 -0.31039532 -0.56752119 0.6327145 ]
Unique values in p90r_150: [-6.28048866e-01 -3.90583101e-01 -1.27851351e-01 -6.61753364e-01
-5.16122769e-01 -4.80893172e-01 8.63833546e-01 -6.12714925e-01
-4.59515362e-01 -3.33345100e-01 3.74509931e-01 -2.19658258e-01
-5.99472076e-01 3.59170851e-01 9.78258162e-01 1.68184071e+00
-7.37976000e-01 -8.42355189e-01 -3.54579026e-01 -8.05488138e-01
6.64979758e-01 -8.09386592e-01 2.87129665e-01 4.83994088e-02
-6.30323116e-01 -4.86067496e-01 1.74165968e-02 -5.07570103e-01
-7.50814358e-01 -1.12501206e-02 -7.18600456e-01 -5.79353932e-02
-6.13413423e-01 -5.94251503e-01 -6.50817800e-01 -4.97711836e-01
7.68348785e-01 -3.83682534e-01 5.16305573e-01 3.89478650e+00
-1.07913117e-01 -7.76827607e-02 -5.07338127e-01 2.51552832e+00
-2.06404030e-01 -3.11285308e-01 1.15988855e-03 3.56417965e-01
-1.12281029e-01 -6.25646147e-01 -3.49300826e-01 -8.06271426e-01
-7.01088799e-01 -7.00344785e-01 -6.58013056e-02 -1.58217517e-01
-6.86809029e-01 -4.90729049e-01 -1.83088923e-01 -5.53060991e-01
-4.74872794e-01 -8.29032726e-01 5.90541726e-01 5.11757805e-01
-5.72561332e-01 -7.50905754e-01 -7.94478430e-01 -6.27543436e-01
-6.38620681e-01 3.31627311e-01 -1.48909093e-01 -6.18671435e-01
-7.26489859e-01 5.06101542e-01 -4.68019944e-01 9.62067523e-01
-6.85006073e-01 1.00361040e+00 -5.78765970e-01 -5.29547675e-01
-6.68923714e-01 -7.05006706e-01 -7.94423006e-01 3.78683306e-01
4.19723327e-01 4.66819697e-01 6.13152095e-01 -1.01192405e-01
3.76558132e-02 -6.73125719e-01 7.68018438e-01 -2.03100567e-01
1.28322285e+00 -6.62862226e-01 -5.94622732e-03 -1.57699975e-01
6.11680219e-01 2.02156884e+00 1.04093587e+00 -4.83454090e-01
-4.21551231e-01 1.50886038e+00 -7.24988986e-01 -5.07925722e-02
-3.31117098e-01 -7.17452319e-01 1.59952576e+00 -1.66645018e-01
-4.22641374e-01 6.76255632e-02 6.91965434e-02 6.54063648e-01
-3.53676079e-01 -8.28191885e-01 -6.44906437e-01 -6.44782741e-01
-3.88586342e-01 2.61190140e-01 -3.35363883e-01 4.51282410e-01
-4.47769716e-01 5.25639691e-01 1.44779403e+00 2.83822893e+00
-6.45372225e-01 -5.37619504e-01 1.92779093e-01 -6.62363771e-01
3.60833594e-01 1.65780252e+00 -7.34605367e-01 -8.01410931e-01
-1.91934862e-01 4.65993832e-01 1.89266410e-01 2.36872982e-01
1.80155454e+00 -3.06102542e-01 -1.56639196e-01 -6.21965722e-01
1.71368982e-01 -6.23895311e-01 -2.04689900e-01 1.01380342e+00
-7.12804713e-01 -7.13300967e-01 -2.05849782e-01 2.02114674e+00
5.02409005e-01 -6.55097987e-01 -5.47018957e-01 -3.01620844e-01
-6.85729164e-01 2.36010773e+00 -6.54204951e-01 -2.68347631e-01
-3.64981264e-01 1.21303166e-01 3.92411030e-01 -5.11953065e-01
7.91597823e-01 6.95852455e-01 3.80401106e-01 -6.21376237e-01
4.19778385e-01 1.04674629e+00 1.65959740e+00 9.92793761e+00
1.58170174e+00 4.48903917e-01 -5.78307890e-01 8.66127618e-01
-1.21240755e-01 -5.10402272e-01 -3.21680205e-01 -3.20281739e-01
-3.70861428e-01 1.63548579e+00 -4.44679143e-01 4.31013829e-01
-4.03848340e-01 3.35973200e-01 -6.78342621e-01 1.61447582e-01
-6.84083672e-01 -5.94985239e-01 5.42399259e-01 -5.36688661e-01
-8.22440042e-01 -1.56499716e-01 -7.33653969e-01 -2.04935824e-01
-3.46423089e-02 -5.35336444e-01 1.67815919e+00 -5.51115618e-01
-6.26564510e-01 -4.23089177e-01 -6.61979101e-01 -7.79254972e-01
-5.97668752e-01 3.02586563e+00 -5.98661993e-01 -5.51263173e-01
2.30781024e+00 -7.25343191e-01 2.69859895e-01 -5.20409563e-01
-6.41828344e-01 -8.00265730e-01 5.80491912e-02 -8.69838442e-02
-3.54990123e-01 -7.67915285e-01 1.76063565e+00 -5.47136046e-01
-3.42018525e-01 -5.22882755e-01 -4.27941597e-01 -4.93096844e-02
-4.95253325e-01 -4.04119959e-01 -3.36586164e-01 -1.10016322e-01
-2.01694760e-01 -3.33389146e-01 -5.15707267e-01 -2.27715037e-01
-4.19348923e-01 -7.86750529e-01 -9.63877020e-02 -9.41670408e-02
-8.69728326e-02 -8.21311212e-01 1.31591618e-01 -6.37225519e-01
-2.11113300e-01 1.81908125e+00 4.10741578e-01 1.34214562e+00
2.68934925e-01 -2.14868236e-01 7.69923435e-01 2.89787479e+00
6.15941686e-01 5.23411688e-01 -5.32641552e-01 -6.20456039e-01
-3.36564141e-01 -2.20590568e-01 -5.20759730e-01 -7.33874200e-01
3.80140500e-01 -8.43883631e-01 -2.63385096e-01 1.64090352e-01
1.59850903e+00 -7.47523375e-01 -6.03700508e-01 -3.09376641e-01
-7.18295803e-01 -4.84370250e-01 -6.42789651e-01 -5.14280171e-01
-7.11544993e-01 -5.20087659e-01 -6.29786800e-02 -7.14201711e-01
-2.01404789e-01 8.05817396e-01 -5.02864871e-01 1.17221181e+00
-2.84960379e-01 1.60052786e-01 -2.86156967e-01 -6.41318876e-01]
Unique values in p00r_150: [-5.65347704e-01 -3.86355084e-01 -1.05791113e-01 -5.86521135e-01
-4.78385625e-01 -4.29111585e-01 7.13388674e-01 -5.73199128e-01
-4.28564196e-01 -3.33829794e-01 1.62558864e-01 -2.35356905e-01
-5.59961335e-01 2.54790916e-01 8.40503246e-01 1.43515125e+00
-6.62714988e-01 -7.52376236e-01 -3.37002846e-01 -7.25460213e-01
5.32560797e-01 -7.22044445e-01 2.09962157e-01 -3.45341626e-03
-5.75135141e-01 -4.48384493e-01 -1.20612599e-02 -4.45515212e-01
-6.69366366e-01 -3.54486087e-02 -6.28324818e-01 -7.73960564e-02
-5.26765496e-01 -5.47777116e-01 -5.85976753e-01 -4.40164634e-01
5.73064581e-01 -3.04300860e-01 4.09130575e-01 3.69636741e+00
-1.88663413e-01 -1.99472718e-02 -4.67495891e-01 2.77500933e+00
-2.60040543e-01 -2.24959520e-01 -2.90754358e-02 2.58523388e-01
-1.37702092e-01 -5.74341427e-01 -3.18830732e-01 -7.18394683e-01
-6.07934875e-01 -6.29053567e-01 -8.19195354e-02 -1.57372007e-01
-5.92172777e-01 -4.12482386e-01 -2.00702965e-01 -4.89720489e-01
-4.37283322e-01 -7.40033545e-01 4.95251118e-01 4.05061249e-01
-5.15738915e-01 -6.69495695e-01 -7.12918987e-01 -5.72992805e-01
-5.80529931e-01 2.72199092e-01 -1.76055419e-01 -5.50920092e-01
-6.44782882e-01 4.28247086e-01 -4.29273997e-01 8.87368172e-01
-5.97059277e-01 8.55033117e-01 -5.29475373e-01 -4.82512999e-01
-6.02717836e-01 -6.34770174e-01 -6.97534347e-01 2.73898404e-01
3.11123869e-01 3.51648707e-01 6.15006014e-01 -1.41193953e-01
-2.69761085e-02 -6.02931980e-01 6.54303737e-01 -2.07906245e-01
1.05554595e+00 -5.95472450e-01 -5.56448596e-02 -2.11674808e-01
4.79608423e-01 2.36085837e+00 8.98321969e-01 -4.02987291e-01
-3.99152560e-01 1.34740659e+00 -6.50342190e-01 -7.94713227e-02
-3.17077282e-01 -6.13275528e-01 1.34849234e+00 -1.75333587e-01
-4.12347043e-01 5.37699218e-03 6.69433512e-03 5.40013710e-01
-3.29324361e-01 -7.39691487e-01 -5.83873215e-01 -5.83808250e-01
-4.06088160e-01 1.46834962e-01 -3.25985889e-01 3.73869094e-01
-4.22067710e-01 4.15936847e-01 1.54433131e+00 3.12209010e+00
-5.98711670e-01 -4.22428626e-01 1.09618520e-01 -5.98101722e-01
2.01378374e-01 1.42712388e+00 -6.67279070e-01 -7.23660145e-01
-2.47850609e-01 2.58935433e-01 9.57322818e-02 1.51439647e-01
1.67003230e+00 -2.20039034e-01 -2.53119981e-01 -5.65026489e-01
1.65181519e-01 -5.71719072e-01 -2.26331000e-01 8.71346515e-01
-6.59160267e-01 -6.59624345e-01 -2.11728945e-01 2.36049745e+00
4.25131179e-01 -6.01688324e-01 -4.96017870e-01 -2.15602776e-01
-6.11195149e-01 2.24337123e+00 -5.93349663e-01 -2.50506349e-01
-2.85271570e-01 -2.63233264e-03 2.85065743e-01 -4.75225506e-01
6.15228579e-01 5.68429820e-01 2.75173640e-01 -5.52471128e-01
3.45254480e-01 8.74113536e-01 1.42860664e+00 1.08379001e+01
1.36492905e+00 3.71787812e-01 -5.29072952e-01 8.72937552e-01
-1.49326590e-01 -4.51578599e-01 -3.21943631e-01 -3.20653357e-01
-3.88896534e-01 1.40187781e+00 -3.55671220e-01 3.14323990e-01
-3.96737431e-01 2.34754070e-01 -6.14853332e-01 8.89199946e-02
-6.21171766e-01 -5.39363265e-01 3.94699955e-01 -4.85445441e-01
-7.25502320e-01 -1.75565175e-01 -6.57779162e-01 -2.08143848e-01
-7.57328357e-02 -4.96239532e-01 1.44232746e+00 -4.87263254e-01
-5.68876860e-01 -3.92776379e-01 -5.97762160e-01 -7.00094443e-01
-5.36669028e-01 2.83883129e+00 -5.51648540e-01 -5.05057008e-01
2.26849398e+00 -6.43003868e-01 1.28118466e-01 -4.77273704e-01
-5.80146458e-01 -7.15008089e-01 -2.50782925e-02 -1.15695246e-01
-3.30407108e-01 -6.80663033e-01 1.68258916e+00 -5.11419353e-01
-3.37360754e-01 -4.77222875e-01 -3.98704423e-01 -1.01147329e-01
-4.12124478e-01 -3.17002091e-01 -3.32719978e-01 -1.49224331e-01
-2.43874519e-01 -3.33865886e-01 -4.78160955e-01 -2.33435028e-01
-4.20061620e-01 -6.94687021e-01 -1.95650143e-01 -1.11583813e-01
-1.15692238e-01 -7.30249717e-01 8.34852030e-02 -5.53074158e-01
-2.24568528e-01 2.17504985e+00 2.96085707e-01 1.59905518e+00
1.97429353e-01 -2.23341414e-01 6.41220537e-01 2.52669921e+00
4.86357550e-01 4.13891657e-01 -4.98977981e-01 -5.66009684e-01
-3.23621890e-01 -2.09545404e-01 -4.84742858e-01 -6.47356212e-01
2.75155594e-01 -7.52589627e-01 -2.65703915e-01 1.23384453e-01
1.34746072e+00 -6.63026578e-01 -5.50589553e-01 -2.99984908e-01
-6.64097897e-01 -4.06166358e-01 -5.52054270e-01 -4.86602176e-01
-6.40063907e-01 -4.39936054e-01 -1.04624152e-01 -6.39267486e-01
-2.43877527e-01 6.38315164e-01 -4.62327576e-01 1.48219664e+00
-2.81142091e-01 1.25441799e-02 -3.28494254e-01 -5.82576023e-01]
Unique values in p10r_150: [-5.35821619e-01 -3.44657370e-01 -6.50994104e-02 -5.47570504e-01
-4.35949800e-01 -3.94570112e-01 6.24709365e-01 -5.59046203e-01
-4.11788883e-01 -2.99552170e-01 5.91494642e-02 -2.22583272e-01
-5.47150280e-01 2.31160409e-01 7.54242520e-01 1.23916693e+00
-6.22855557e-01 -7.10776494e-01 -3.18415416e-01 -6.85230683e-01
4.45298286e-01 -6.80967370e-01 1.89571813e-01 -9.98005880e-03
-5.36536992e-01 -4.23525180e-01 -4.92813885e-02 -4.09081125e-01
-6.29059297e-01 -6.99337364e-02 -5.88648081e-01 -7.32494681e-02
-4.85189486e-01 -5.09575112e-01 -5.47362669e-01 -4.03550442e-01
5.31847453e-01 -2.70128400e-01 3.53263967e-01 3.52089115e+00
-2.34622217e-01 -1.38796592e-02 -4.44215024e-01 3.20187920e+00
-3.01282350e-01 -2.00216814e-01 -2.76836018e-02 2.34585950e-01
-1.30262376e-01 -5.36162834e-01 -2.75326974e-01 -6.77060538e-01
-5.68638792e-01 -5.89297835e-01 -7.74249330e-02 -1.48873861e-01
-5.53308488e-01 -3.76424650e-01 -1.89870553e-01 -4.52638804e-01
-4.00952493e-01 -6.98260410e-01 4.42287880e-01 3.68760594e-01
-4.77902108e-01 -6.29188123e-01 -6.73634193e-01 -5.34404800e-01
-5.41623882e-01 2.24968186e-01 -1.69555670e-01 -5.12636138e-01
-6.05066309e-01 3.63334364e-01 -3.93134545e-01 8.59914726e-01
-5.58217806e-01 7.68742819e-01 -4.92803349e-01 -4.56097825e-01
-5.70686885e-01 -5.94943685e-01 -6.56445151e-01 2.05063083e-01
2.38678388e-01 2.74838076e-01 5.90451269e-01 -1.38235666e-01
-6.32969165e-02 -5.63722242e-01 5.91715425e-01 -1.95979748e-01
8.92978302e-01 -5.56417723e-01 -5.67404456e-02 -2.31060082e-01
3.82974316e-01 2.26592154e+00 7.61964050e-01 -3.67264874e-01
-3.63737557e-01 1.28692900e+00 -6.10285506e-01 -1.10327811e-01
-3.03550868e-01 -5.74071449e-01 1.15377479e+00 -1.70924280e-01
-4.07259883e-01 -2.13800528e-03 -9.03310383e-04 5.18683623e-01
-2.94508937e-01 -6.98034871e-01 -5.52752741e-01 -5.52701318e-01
-4.21154888e-01 9.17336251e-02 -2.92232385e-01 3.00932723e-01
-3.78902075e-01 3.32073282e-01 1.66955319e+00 3.30427049e+00
-5.80618278e-01 -3.44052074e-01 5.85870219e-02 -5.58885238e-01
7.82510782e-02 1.24084355e+00 -6.25231475e-01 -6.86452254e-01
-2.41850940e-01 1.42990872e-01 4.27663217e-02 9.43985306e-02
1.80038264e+00 -1.95454802e-01 -2.89969224e-01 -5.26664790e-01
1.97614739e-01 -5.33214029e-01 -2.17933749e-01 7.82340533e-01
-6.30882681e-01 -6.31355133e-01 -1.79192183e-01 2.26554658e+00
3.60650710e-01 -5.74145906e-01 -4.67916346e-01 -1.91185597e-01
-5.73696488e-01 2.39389057e+00 -5.54128047e-01 -2.36794316e-01
-2.51532984e-01 -1.51732766e-02 2.15010278e-01 -4.38220996e-01
5.05851902e-01 5.14309964e-01 2.06196003e-01 -5.14198121e-01
3.17982761e-01 7.44196228e-01 1.24207824e+00 1.13023884e+01
1.17789553e+00 2.99135586e-01 -4.92408836e-01 8.35507406e-01
-1.41363917e-01 -4.15168894e-01 -3.45415328e-01 -3.44341330e-01
-4.02353243e-01 1.20501329e+00 -3.20815170e-01 2.41046003e-01
-3.93410409e-01 2.12415008e-01 -5.83901067e-01 4.04281684e-02
-5.87891194e-01 -5.00843061e-01 2.84359421e-01 -4.48323532e-01
-6.84013665e-01 -1.66783633e-01 -6.17626450e-01 -1.75616656e-01
-7.28343320e-02 -4.58927981e-01 1.25039703e+00 -4.50172628e-01
-5.30021499e-01 -3.57373924e-01 -5.58537059e-01 -6.59070150e-01
-4.98625163e-01 2.70556398e+00 -5.13485158e-01 -4.68730280e-01
2.42027179e+00 -6.03351663e-01 6.95358999e-02 -4.55360757e-01
-5.41276774e-01 -6.73849796e-01 -1.07097785e-01 -1.09518966e-01
-2.95572221e-01 -6.39755343e-01 1.60572401e+00 -4.69100153e-01
-3.03333926e-01 -4.40039559e-01 -3.79788591e-01 -1.29319615e-01
-3.76290735e-01 -2.82724430e-01 -3.36094854e-01 -1.72507154e-01
-2.37787964e-01 -2.99586988e-01 -4.41343890e-01 -2.25430302e-01
-4.28881774e-01 -6.53833811e-01 -2.52325760e-01 -1.05747923e-01
-1.09513609e-01 -6.88641816e-01 3.50742528e-02 -5.14648878e-01
-1.92567598e-01 2.07828005e+00 2.24756601e-01 1.72802844e+00
1.55329787e-01 -1.90719573e-01 5.34777509e-01 2.40835337e+00
4.38369532e-01 3.30249362e-01 -4.84561426e-01 -5.36297820e-01
-3.09078873e-01 -1.98122386e-01 -4.41820627e-01 -6.07336701e-01
2.06185289e-01 -7.10558561e-01 -2.57944827e-01 7.52808469e-02
1.15283203e+00 -6.22801456e-01 -5.08161239e-01 -2.66670718e-01
-6.35617375e-01 -3.70213679e-01 -5.13713349e-01 -4.86030204e-01
-5.99927193e-01 -4.03684356e-01 -1.04821233e-01 -5.99323237e-01
-2.37801355e-01 5.22821592e-01 -4.33121518e-01 1.41849766e+00
-2.48415446e-01 4.30481507e-04 -3.60743221e-01 -5.43480745e-01]
Unique values in p90_600: [-1.06983350e+00 -7.66523641e-01 -4.79746196e-01 -1.01724411e+00
-6.69230895e-01 -1.08823641e+00 1.47585211e+00 -1.04640204e+00
-3.22419800e-01 3.19455906e-02 -1.33247125e-01 1.11518381e+00
-1.13432090e+00 3.13426818e-01 1.41494150e+00 1.56630658e+00
-8.11516034e-01 -1.51652656e+00 -4.26247010e-01 -1.25344063e+00
6.26732975e-01 -1.24548070e+00 1.36933656e+00 9.20217320e-01
-5.66732256e-01 -1.42630873e-01 5.50106152e-01 -8.52394621e-01
-6.37754121e-01 5.32928343e-01 -1.05896188e+00 6.84342683e-01
-1.11256124e+00 -6.40856308e-01 -8.38396185e-01 -2.89090580e-01
3.38355990e-01 -7.66728921e-01 1.58831256e+00 2.56867936e+00
-2.48497743e-01 1.52356120e-01 -4.73019589e-01 9.15175650e-01
-2.89598032e-01 1.67201951e-01 2.35519050e-01 1.54339736e+00
2.10540610e-01 -6.02828646e-01 -5.90166991e-01 -1.32108769e+00
-1.12915770e+00 -1.13218763e+00 6.77658774e-01 1.54852321e-01
-1.15286176e+00 -9.29075638e-01 1.13444726e+00 -1.11448059e-01
-3.45636118e-01 -9.83875476e-01 1.50789217e+00 1.44868949e+00
-5.40374337e-01 -6.37540630e-01 -1.16079049e+00 -5.73577103e-01
-8.60047450e-01 8.66401182e-01 9.57200519e-01 -1.16652682e+00
-1.22378838e+00 1.29472969e+00 -4.29744977e-01 9.22253695e-01
-1.00288767e+00 1.44579916e+00 -7.79480466e-02 3.15069056e-01
-1.19356791e+00 -1.17229108e+00 -1.41193285e+00 2.73569703e-01
-8.51853893e-02 -7.56160687e-02 8.51358283e-01 -4.14370345e-01
-5.64659319e-02 -1.02783490e+00 1.37363922e+00 -3.22442791e-01
1.58832899e+00 -1.06033479e+00 1.16770258e+00 3.41985336e-01
9.71061007e-01 1.20110570e+00 1.67315058e+00 -9.41873598e-01
-4.12655849e-01 3.47714897e+00 -1.19147078e+00 1.13379244e-01
-6.38477915e-02 -9.84773780e-01 1.53973517e+00 -2.06492580e-01
-1.05783695e+00 2.34484440e-01 2.35289136e-01 1.99227026e+00
-1.93922891e-01 -1.28900657e+00 -5.72166421e-01 -5.72225542e-01
-7.16364767e-01 -9.76417641e-02 -2.17369122e-01 1.42719260e+00
-5.71113747e-01 -8.80490199e-03 1.18609564e+00 1.32517678e+00
-6.94059891e-01 -6.99962094e-01 8.90626267e-02 -7.91383839e-01
2.41104733e-02 1.57515824e+00 -1.44288230e+00 -1.46150462e+00
1.47544362e-01 -7.98037755e-02 6.98285283e-01 7.02686481e-01
3.54696258e-01 1.26556561e-01 -1.57879052e-01 -8.96344193e-01
-6.59085149e-01 -5.78564580e-01 -3.16993845e-01 1.41935912e+00
-1.13846098e+00 -1.13695012e+00 -1.51415204e-01 1.20616379e+00
1.29582999e+00 -1.14451919e+00 1.06064509e+00 -1.26280319e-02
-4.96485527e-01 1.32090696e+00 -7.44729501e-01 -2.26551045e-03
-7.00214999e-01 -5.98967745e-01 2.83833690e-01 -4.38417635e-01
5.51403520e-01 1.54012930e+00 2.77938056e-01 -1.20210262e+00
1.18231850e+00 1.57448492e+00 1.57532246e+00 3.18601303e+00
1.64920675e+00 1.42655213e+00 -7.70595959e-02 1.68579581e+00
1.39617072e+00 -2.55464116e-01 -2.96570974e-01 -2.95426334e-01
-5.01929546e-01 1.62657671e+00 -8.36824563e-01 3.42494430e-01
-1.12663522e+00 3.02226755e-01 -1.16769281e+00 -2.86162470e-01
-7.68044353e-01 -3.83437151e-01 3.71463508e-01 -5.09565953e-01
-1.09714884e+00 9.78089786e-01 -1.26392303e+00 -1.19123879e-01
1.10452569e+00 -1.33375220e-01 1.57607789e+00 -1.15666968e-01
-5.74780864e-01 -3.36584102e-01 -7.82972296e-01 -1.21200204e+00
-1.06709424e+00 2.19871599e+00 -6.89543737e-01 -1.83036063e-02
2.78269581e+00 -1.06844252e+00 8.46612215e-01 -8.04776289e-01
-1.12564003e+00 -1.01856447e+00 -1.83972139e-02 9.33683671e-01
-1.94589640e-01 -1.05151433e+00 1.57870547e+00 -6.90552071e-01
1.01251749e-02 -5.93006421e-01 -4.13422774e-01 -4.96966703e-01
-7.70951114e-01 -7.66525283e-01 1.68712810e-01 5.15126484e-01
1.86136954e-01 3.19981422e-02 -3.73383370e-01 1.00922662e+00
-3.93098437e-01 -1.10647675e+00 -2.57305065e-01 4.19925950e-01
9.33962852e-01 -1.21431759e+00 6.25419185e-01 -4.76632513e-01
-4.86390258e-02 9.61700251e-01 3.83813137e-01 9.82244648e-01
1.32869117e+00 -4.27844475e-02 1.31870636e+00 4.45584068e+00
1.50933734e+00 -8.62918252e-03 -1.26220361e+00 -5.34813719e-01
-2.05607414e-01 6.68234403e-02 -6.34180611e-01 -1.32896386e+00
2.73142721e-01 -1.20441490e+00 4.70508953e-02 6.64290957e-01
1.53935745e+00 -1.06563594e+00 -6.55940264e-01 -3.62588940e-01
-1.13229437e+00 -9.25669636e-01 -9.50582386e-01 -7.50221145e-01
-1.20078391e+00 -7.62207839e-01 3.45811751e-01 -1.15436605e+00
1.85266568e-01 1.12507008e+00 -4.07807962e-01 9.12449535e-01
-3.32271585e-01 1.05560549e-01 -4.52302757e-01 -6.11136728e-01]
Unique values in p00_600: [-1.06620192 -0.76785878 -0.39838346 -0.96784484 -0.65392596 -1.04695935
1.34206364 -1.01534087 -0.36752027 0.03340385 -0.17304796 1.02150933
-1.13876359 0.25500496 1.28434344 1.42329836 -0.77753186 -1.47767697
-0.44440495 -1.22261704 0.4819216 -1.18420999 1.26055864 0.835165
-0.55101914 -0.18717168 0.46322711 -0.7914664 -0.61661655 0.44695013
-0.98304069 0.61014032 -1.00815138 -0.62162277 -0.80444293 -0.28622098
0.27204773 -0.69263633 1.45097222 2.65596389 -0.28944484 0.35254668
-0.49273435 1.44531131 -0.40555043 0.30801023 0.17504657 1.42562578
0.15069117 -0.5811856 -0.56432902 -1.25847293 -1.0551579 -1.10479066
0.60342832 0.10579435 -1.06152003 -0.84278992 1.04041405 -0.12839138
-0.3366751 -0.90126691 1.3830714 1.33484111 -0.52843559 -0.61641534
-1.13822152 -0.5578918 -0.83122186 0.72409416 0.87004638 -1.13245401
-1.17489427 1.16732641 -0.41844438 1.19117127 -0.91790426 1.31622169
-0.09560469 0.25282769 -1.18018729 -1.14422629 -1.35458261 0.20845641
-0.1232335 -0.11426765 1.03996358 -0.47335064 -0.08022866 -1.01372219
1.24701451 -0.34348921 1.44505605 -0.99710736 1.07262264 0.25345834
0.8699713 1.51905322 1.52270202 -0.85940925 -0.42195954 3.54520627
-1.16013538 0.0602969 -0.10134968 -0.88784591 1.39988894 -0.23869642
-1.04860356 0.17835001 0.17914584 2.09105976 -0.19330558 -1.22280173
-0.58535244 -0.585405 -0.7720046 -0.17411257 -0.22412823 1.27623499
-0.57911043 -0.05237611 1.53142612 1.73158486 -0.77043396 -0.5007392
0.03744306 -0.7659593 -0.10554356 1.4326381 -1.40893885 -1.42980717
0.13399375 -0.13664399 0.5712798 0.60991509 0.46564463 0.26542582
-0.29732957 -0.86672488 -0.5295062 -0.56121327 -0.38178064 1.28868297
-1.15112298 -1.14980911 -0.15533849 1.52406845 1.16836249 -1.15194584
0.96401437 0.11582481 -0.35769702 1.52246177 -0.74360098 -0.04633681
-0.63113819 -0.5597132 0.21770606 -0.44803724 0.4109576 1.41837322
0.21242055 -1.17005172 1.07904934 1.4298602 1.43277324 3.944803
1.5021606 1.2755743 -0.0947548 1.87707159 1.29153594 -0.24699557
-0.41051761 -0.40950105 -0.59208246 1.48046297 -0.76154019 0.26978037
-1.11493824 0.24431381 -1.16808917 -0.31048028 -0.78844675 -0.38782144
0.24605562 -0.49406024 -1.00795918 0.88826037 -1.23213847 -0.1204436
1.01149389 -0.12825774 1.43316364 -0.13239756 -0.5802336 -0.31636792
-0.75801601 -1.18797141 -1.03203829 2.3126008 -0.66855421 -0.03949267
3.4453221 -0.99401413 0.74359951 -0.80932752 -1.06535653 -0.99010105
-0.13636019 0.84932477 -0.19396777 -0.97027588 1.71143385 -0.69910958
0.00742976 -0.59912631 -0.43633854 -0.55147862 -0.70442813 -0.70624352
0.11059936 0.45172511 0.17199839 0.03347893 -0.38165 0.9211747
-0.49820456 -1.03065685 -0.38402548 0.35834273 0.84959505 -1.14200697
0.53491187 -0.45697306 -0.06120982 1.27360724 0.3060582 1.36128368
1.1730774 -0.0466131 1.19285303 4.53966338 1.39199071 -0.05222145
-1.24359241 -0.55039899 -0.24004633 0.02068559 -0.64204407 -1.26750485
0.208066 -1.13769447 0.05409543 0.57170023 1.39954358 -1.00296347
-0.63486358 -0.36797374 -1.14564977 -0.83969369 -0.85709684 -0.79742761
-1.14945774 -0.69787679 0.28497621 -1.12010964 0.17112748 1.01532288
-0.43186537 1.22378529 -0.33777275 0.12053972 -0.54902356 -0.59529431]
Unique values in p10_600: [-1.06882346e+00 -7.21464537e-01 -3.27728687e-01 -9.34511551e-01
-6.03926002e-01 -1.02140110e+00 1.25125896e+00 -1.04560483e+00
-4.13511049e-01 9.86909013e-02 -2.39266065e-01 9.75164081e-01
-1.15494963e+00 2.52476098e-01 1.20577873e+00 1.32790598e+00
-7.37630295e-01 -1.46022450e+00 -4.18503911e-01 -1.21570874e+00
3.62338704e-01 -1.14656364e+00 1.18752209e+00 7.96288280e-01
-5.04115073e-01 -1.79009323e-01 3.81128591e-01 -7.52498021e-01
-5.72119311e-01 3.66380143e-01 -9.50012155e-01 5.81670998e-01
-9.28870375e-01 -5.76940973e-01 -7.65572359e-01 -2.31244930e-01
2.34429947e-01 -6.50540078e-01 1.36589271e+00 2.66643639e+00
-3.54155212e-01 4.12758469e-01 -4.84568819e-01 1.91270790e+00
-5.19969304e-01 3.28098729e-01 1.72755895e-01 1.34474531e+00
1.57754857e-01 -5.35332388e-01 -4.95764168e-01 -1.23392188e+00
-1.02430869e+00 -1.07557604e+00 5.74303791e-01 1.04753061e-01
-1.03083814e+00 -8.05529287e-01 9.93968001e-01 -6.81545999e-02
-2.83378098e-01 -8.65249976e-01 1.29346955e+00 1.25733515e+00
-4.80928717e-01 -5.71910222e-01 -1.12442834e+00 -5.11197415e-01
-7.93298319e-01 5.97570134e-01 8.28311076e-01 -1.10395312e+00
-1.14839913e+00 1.07503535e+00 -3.67731923e-01 1.24369529e+00
-8.82903209e-01 1.23784362e+00 -3.41573926e-02 2.49388887e-01
-1.17403420e+00 -1.11624583e+00 -1.33308927e+00 1.19515541e-01
-1.91414298e-01 -1.83011471e-01 1.05959930e+00 -4.81602290e-01
-1.22968028e-01 -9.82085469e-01 1.17085115e+00 -3.14989733e-01
1.33868315e+00 -9.64482754e-01 1.01444182e+00 1.63059246e-01
7.73302592e-01 1.53742936e+00 1.41695798e+00 -8.22660500e-01
-3.71005770e-01 3.53913475e+00 -1.13253928e+00 -1.95352396e-02
-1.01500686e-01 -8.52028294e-01 1.30176292e+00 -2.34733478e-01
-1.05829607e+00 1.77695432e-01 1.78481268e-01 2.08949282e+00
-1.35137251e-01 -1.19743807e+00 -5.75497000e-01 -5.75550325e-01
-8.24785062e-01 -2.25036830e-01 -1.66809228e-01 1.15544316e+00
-5.24837274e-01 -1.25042072e-01 1.81287873e+00 2.03306703e+00
-8.27099067e-01 -3.47985000e-01 -4.09352236e-02 -7.25830133e-01
-2.37107824e-01 1.33939882e+00 -1.38767326e+00 -1.41558866e+00
8.80400240e-02 -2.12927947e-01 4.87188315e-01 5.15660818e-01
6.33929058e-01 2.85579417e-01 -4.17381289e-01 -8.29866331e-01
-4.75328236e-01 -5.14612993e-01 -3.87498492e-01 1.20998856e+00
-1.16370608e+00 -1.16256241e+00 -9.60110643e-02 1.54246713e+00
1.07610184e+00 -1.15981900e+00 9.05168592e-01 1.35667267e-01
-3.27401724e-01 1.79396255e+00 -7.02611502e-01 -4.02335848e-02
-5.87097896e-01 -5.13671394e-01 1.28454420e-01 -3.97879940e-01
2.91767871e-01 1.33175096e+00 1.23332457e-01 -1.14280566e+00
1.01357179e+00 1.33548368e+00 1.33951109e+00 4.48063581e+00
1.40407589e+00 1.15476959e+00 -3.32733277e-02 1.89447933e+00
1.22875038e+00 -1.90642495e-01 -5.14316902e-01 -5.13442660e-01
-6.70153690e-01 1.38203040e+00 -7.21835002e-01 1.79014513e-01
-1.12051740e+00 2.42162007e-01 -1.16917465e+00 -3.66801550e-01
-8.11745807e-01 -3.36043107e-01 1.39428051e-01 -4.45317740e-01
-9.74886655e-01 8.46694013e-01 -1.20690879e+00 -6.00955764e-02
9.62324090e-01 -6.82668621e-02 1.33921640e+00 -7.23026886e-02
-5.34093293e-01 -2.62281222e-01 -7.17639202e-01 -1.16114931e+00
-1.00030563e+00 2.32493474e+00 -6.25375100e-01 2.36436133e-02
3.89924386e+00 -9.61253813e-01 6.30603290e-01 -8.24455292e-01
-1.03478135e+00 -9.57718956e-01 -2.59786194e-01 8.12313711e-01
-1.35817841e-01 -9.36237582e-01 1.72736299e+00 -6.57623824e-01
7.18321673e-02 -5.53638144e-01 -4.29177241e-01 -5.79566505e-01
-6.62867872e-01 -6.64543386e-01 2.75868234e-02 3.72624729e-01
1.24525243e-01 9.87750979e-02 -3.29409814e-01 8.73258059e-01
-5.91017251e-01 -9.98384539e-01 -5.05881800e-01 3.44152226e-01
8.12552268e-01 -1.12048232e+00 4.48205262e-01 -4.06990018e-01
1.21923663e-03 1.29177158e+00 2.14208716e-01 1.62816530e+00
1.03745557e+00 1.61080124e-02 1.09783861e+00 4.54702488e+00
1.30771281e+00 -1.24897534e-01 -1.24135926e+00 -5.42031635e-01
-2.35357937e-01 2.39102360e-02 -5.91358247e-01 -1.24323965e+00
1.19136656e-01 -1.11888680e+00 2.08370580e-02 4.88521429e-01
1.30139807e+00 -9.70500009e-01 -5.81517061e-01 -3.15131464e-01
-1.15878619e+00 -8.02331217e-01 -8.20389997e-01 -8.59033456e-01
-1.12158249e+00 -6.56161608e-01 2.81664272e-01 -1.09144430e+00
1.23669243e-01 9.17741960e-01 -4.24175959e-01 1.24495824e+00
-2.83996943e-01 9.93364090e-02 -6.49999816e-01 -5.49781937e-01]
Unique values in p90u_600: [-1.16208916 -0.90181161 -0.41087373 -1.05698568 -0.71049175 -1.06853125
1.7845972 -1.17464161 -0.43184172 0.35133535 -0.50342476 1.40944072
-1.23104685 0.63970116 1.59813772 1.75282451 -0.71389525 -1.62079936
-0.40896936 -1.42854449 0.15935667 -1.38319232 1.74588821 1.35531775
-0.44790707 0.03459041 0.61881273 -0.87979944 -0.51169859 0.60443794
-1.08323917 0.79284904 -1.26714043 -0.53624909 -0.80809458 -0.04417256
0.27999098 -0.75247994 1.86937411 1.93180075 -0.57969663 -0.79679017
-0.29362055 -0.65778586 -0.64611847 0.0670816 0.3877944 1.88304781
0.37808607 -0.51474409 -0.70401041 -1.35831166 -1.13972148 -1.18375326
0.78014244 0.18964266 -1.13680277 -0.97621391 1.44302829 0.22012754
-0.16371298 -0.83941729 1.89100341 1.82688621 -0.41074196 -0.5113207
-1.15533187 -0.45488563 -0.82770515 0.44136794 1.35230953 -1.20375167
-1.31031948 1.59639743 -0.27557127 -0.10705167 -1.00931917 1.64442939
0.29452488 0.60131537 -1.2935431 -1.23428627 -1.4889867 0.60600172
0.17270468 0.18742006 0.55748744 -0.49991683 0.15841194 -1.01475633
1.56795614 -0.26939324 1.70330087 -1.08970061 1.54361696 0.28285003
1.00743407 0.7817982 1.81644448 -0.9718085 -0.15454663 3.0435965
-1.251448 0.41779449 0.20302796 -0.99796752 1.70556324 0.03571911
-1.17456206 0.54673246 0.54764984 1.4919304 0.11057141 -1.29984791
-0.42522862 -0.42527835 -0.87842213 0.06601256 0.10084817 1.35223495
-0.64333898 0.27608776 -0.14949731 -0.04801363 -0.65744278 -1.16767051
0.37604745 -0.70632997 -0.43575488 1.7715699 -1.52388545 -1.56969481
0.25939094 -0.4862506 0.4458181 0.74788247 -0.73188486 0.04635973
-0.19952066 -0.86461916 -0.84854883 -0.4644423 -0.32667857 1.60248844
-1.23091508 -1.2294433 0.16805562 0.78739945 1.59960453 -1.22445861
1.19657857 -0.0726412 -0.50981908 -0.18456164 -0.58704065 0.03618153
-0.66685028 -0.93611518 0.62121184 -0.18442739 0.0640883 1.92747489
0.61228416 -1.25650976 1.34069932 1.86887689 1.77174393 0.26148674
1.8392174 1.35071841 0.29558397 1.49593306 1.71667623 -0.01447081
-0.31678379 -0.31583657 -0.53793468 1.80806624 -0.87208002 0.69269046
-1.26608383 0.62681557 -1.23982039 -0.10563209 -0.88283003 -0.13648741
-0.1176724 -0.35778996 -1.01635491 1.36302474 -1.34698984 0.20054432
1.48690842 0.13912706 1.77084892 0.21380532 -0.36017415 -0.1764693
-0.69534378 -1.23344596 -1.07368747 1.8639295 -0.60658658 0.36155582
0.35834872 -0.96546142 0.83051385 -0.88939589 -1.15248277 -1.01056224
-0.49033779 1.22961919 0.10969132 -0.94149516 1.37244716 -0.79179554
0.3430292 -0.38976403 -0.22167951 -0.41617912 -0.78954062 -0.73446298
0.46138374 0.90562719 0.2821564 0.35139005 -0.10138828 1.4638123
-0.47875244 -1.08928295 -0.55041752 0.4704407 1.22984294 -1.26693657
0.69081095 -0.29620363 0.31658676 0.45459662 0.74754435 -0.20354818
1.121597 0.30303986 1.54896214 3.7720067 1.83506557 0.27626428
-1.39075313 -0.37235369 0.00689993 0.1089952 -0.71646591 -1.36647859
0.60541996 -1.26200658 0.01400031 0.74898879 1.70511574 -0.96051651
-0.70688686 -0.07678308 -1.2223106 -0.9719328 -0.97920224 -0.85782954
-1.24661 -0.78695505 0.66113406 -1.21583424 0.28155973 1.21634328
-0.24177984 0.37642534 -0.04184555 0.04384129 -0.65146613 -0.49218747]
Unique values in p00u_600: [-1.19885574 -0.93195859 -0.32698204 -1.03834114 -0.7138696 -1.06051803
1.71083782 -1.17224347 -0.48175464 0.36973818 -0.52027615 1.36137659
-1.27963807 0.59279945 1.52717468 1.67582043 -0.69628013 -1.64201818
-0.43963637 -1.44773129 0.06049231 -1.37883422 1.69627496 1.30782896
-0.44209994 -0.01845125 0.55886299 -0.84135999 -0.50008295 0.54464222
-1.03388438 0.74937994 -1.21052504 -0.52954127 -0.7953076 -0.04456462
0.23393768 -0.69129834 1.79614818 2.10534178 -0.60311343 -0.68635695
-0.33356503 -0.43998797 -0.749823 0.23146699 0.3357542 1.83147441
0.32527274 -0.50440429 -0.69735868 -1.33394116 -1.08976017 -1.19862055
0.73638501 0.14982705 -1.06188167 -0.90869602 1.39568128 0.20816165
-0.15224667 -0.75876265 1.83128435 1.77578867 -0.40751017 -0.49971709
-1.17787619 -0.44945027 -0.82112878 0.35412764 1.30504943 -1.20927544
-1.30587498 1.52204323 -0.26540227 0.12505592 -0.94274176 1.57582843
0.28348943 0.55176923 -1.32596128 -1.25061687 -1.47777831 0.55514506
0.13574882 0.15010738 0.78263933 -0.56722892 0.15530772 -1.04107554
1.4985716 -0.29869492 1.62932855 -1.05359295 1.49788266 0.21316719
0.95166834 1.15279266 1.73780169 -0.90920203 -0.17540234 3.27764049
-1.26459769 0.37276241 0.16246562 -0.91640269 1.631823 -0.00555848
-1.20390167 0.49875138 0.49968977 1.68164083 0.11556749 -1.26552896
-0.46218624 -0.46223613 -0.96033598 -0.01912356 0.0966524 1.26749007
-0.66837787 0.23597601 0.08544161 0.22940966 -0.77322099 -1.07505477
0.33201252 -0.70008833 -0.5361884 1.69515839 -1.54825616 -1.5962048
0.26668156 -0.51493089 0.3568953 0.68948451 -0.66971537 0.20838972
-0.3466621 -0.85897322 -0.75276409 -0.45713794 -0.39903377 1.53168846
-1.29177299 -1.29043074 0.17028633 1.1585893 1.52525039 -1.28011082
1.14778 0.07291944 -0.37695666 -0.05578492 -0.61371605 -0.00592433
-0.60798118 -0.93325095 0.56946085 -0.20745252 -0.03137015 1.87207463
0.56111512 -1.2677312 1.29131805 1.78664549 1.69532469 0.6918198
1.76162967 1.26596964 0.28454898 1.77393565 1.67099782 -0.00676294
-0.44661371 -0.44569195 -0.6500947 1.73084098 -0.81554832 0.63521468
-1.29602069 0.5799827 -1.29044262 -0.1350088 -0.92993927 -0.14920344
-0.20629794 -0.93823511 1.31383941 -1.36354202 0.20692868 1.44003506
0.1581514 1.6941131 0.20189226 -0.38551145 -0.15211364 -0.68924339
-1.25684588 -1.07076193 2.07063323 -0.60093019 0.3487705 0.7897901
-0.9030633 0.76876541 -0.92161967 -1.12281764 -1.01505719 -0.57993163
1.18469793 0.11464811 -0.87054749 1.57967702 -0.82116679 0.35451488
-0.41711976 -0.26225688 -0.49580436 -0.74023717 -0.68957123 0.41397555
0.88332028 0.28918629 0.36983796 -0.11803938 1.41746619 -0.59593653
-1.0343809 -0.6723975 0.42858355 1.18493549 -1.22051949 0.63022102
-0.28571188 0.3138125 0.801811 0.68544112 0.05555329 1.0334627
0.31082391 1.47730935 4.03528954 1.78339082 0.23614231 -1.42006565
-0.4102992 -0.03707651 0.06812534 -0.74281953 -1.34359589 0.55460103
-1.22135335 0.0362177 0.68719199 1.63139538 -0.91613662 -0.70466149
-0.08789449 -1.28361019 -0.90461699 -0.90196336 -0.93532016 -1.23381374
-0.74026093 0.61356994 -1.22398322 0.28856624 1.15709263 -0.2834835
0.71752219 -0.05129253 0.07772543 -0.75549848 -0.48817133]
Unique values in p10u_600: [-1.23376266e+00 -9.07064174e-01 -2.45380816e-01 -1.02670392e+00
-6.72779408e-01 -1.05793120e+00 1.66066940e+00 -1.23357725e+00
-5.39112338e-01 4.71793810e-01 -5.72928545e-01 1.34915192e+00
-1.33236599e+00 6.05669184e-01 1.48777708e+00 1.62269397e+00
-6.62119279e-01 -1.66864645e+00 -4.16611277e-01 -1.47918254e+00
-3.13518967e-02 -1.38377130e+00 1.66364517e+00 1.29819756e+00
-3.91745274e-01 -7.72427226e-03 4.87743944e-01 -8.17056247e-01
-4.53977809e-01 4.74575011e-01 -1.02193124e+00 7.45940177e-01
-1.15161535e+00 -4.84779331e-01 -7.67617240e-01 3.05693267e-02
2.07648323e-01 -6.57554904e-01 1.75557361e+00 2.18852545e+00
-6.59422773e-01 -6.70611673e-01 -3.35512352e-01 -2.42865145e-01
-8.61484513e-01 2.67779505e-01 3.45822542e-01 1.79494535e+00
3.47553067e-01 -4.58191959e-01 -6.39798705e-01 -1.34089501e+00
-1.08117427e+00 -1.19697755e+00 7.31954052e-01 1.60459456e-01
-1.05162715e+00 -8.88927992e-01 1.38383110e+00 2.99959038e-01
-8.39543776e-02 -7.28863541e-01 1.78427836e+00 1.74115256e+00
-3.55163888e-01 -4.53586380e-01 -1.19633891e+00 -3.99560107e-01
-7.95179750e-01 2.58334865e-01 1.29341343e+00 -1.20811609e+00
-1.31219026e+00 1.46509255e+00 -2.04342641e-01 1.64609513e-01
-9.25108794e-01 1.53783871e+00 3.80252216e-01 5.63855019e-01
-1.35548316e+00 -1.25227883e+00 -1.49390002e+00 4.53774370e-01
4.83827517e-02 6.22544243e-02 8.35922925e-01 -5.84035039e-01
1.06332465e-01 -1.03007112e+00 1.45991928e+00 -2.67472485e-01
1.56700127e+00 -1.04273188e+00 1.47452345e+00 1.25919907e-01
8.78682470e-01 1.21640963e+00 1.67856980e+00 -8.89486522e-01
-1.08252695e-01 3.37750633e+00 -1.26700890e+00 2.77274505e-01
1.65612119e-01 -8.97289910e-01 1.57579124e+00 -3.03399882e-03
-1.24549178e+00 5.11060257e-01 5.12010215e-01 1.73794789e+00
2.01293906e-01 -1.26862726e+00 -4.65697770e-01 -4.65745840e-01
-1.03386408e+00 -8.33523562e-02 1.81349371e-01 1.18379059e+00
-6.23324377e-01 1.45182304e-01 2.69551234e-01 4.31243203e-01
-8.65705531e-01 -9.96943914e-01 2.37902761e-01 -6.66331140e-01
-6.50644247e-01 1.64430265e+00 -1.56686478e+00 -1.62501731e+00
2.20148851e-01 -5.77174742e-01 2.99718688e-01 6.10636433e-01
-5.88072932e-01 2.44028272e-01 -4.85784226e-01 -8.35375554e-01
-7.15973873e-01 -4.07718299e-01 -4.11605114e-01 1.49233230e+00
-1.34058828e+00 -1.33937966e+00 2.59454212e-01 1.22242984e+00
1.46836590e+00 -1.32438864e+00 1.11887300e+00 1.03686317e-01
-3.57208014e-01 1.07293868e-01 -5.74274509e-01 7.54830185e-03
-5.68927277e-01 -9.27938065e-01 4.68023736e-01 -1.42334433e-01
-1.22220508e-01 1.82907516e+00 4.59703022e-01 -1.27040356e+00
1.25907761e+00 1.73584196e+00 1.64441711e+00 9.70130212e-01
1.70873955e+00 1.18223404e+00 3.81380720e-01 1.85546796e+00
1.64938435e+00 7.10031920e-02 -5.74118854e-01 -5.73301661e-01
-7.54111817e-01 1.67683012e+00 -7.89958416e-01 5.34117907e-01
-1.33452686e+00 5.92923726e-01 -1.32965575e+00 -2.13095986e-01
-9.76752161e-01 -8.07428336e-02 -2.88174697e-01 -2.90232557e-01
-9.19054243e-01 1.30181426e+00 -1.37238783e+00 2.98322364e-01
1.42404979e+00 2.46418045e-01 1.64256297e+00 2.93272709e-01
-3.31529396e-01 -8.35881289e-02 -6.54798882e-01 -1.25878661e+00
-1.06062084e+00 2.15476189e+00 -5.60750773e-01 4.49596845e-01
1.05924312e+00 -8.82818505e-01 6.73651825e-01 -9.61383446e-01
-1.11629066e+00 -1.00227283e+00 -6.86264230e-01 1.17658007e+00
2.00318769e-01 -8.47457185e-01 1.65290950e+00 -7.94003176e-01
4.55449958e-01 -3.65210550e-01 -2.63375077e-01 -5.44617515e-01
-7.09740777e-01 -6.55712215e-01 3.17065146e-01 8.06027868e-01
2.42007036e-01 4.71901395e-01 -4.72196250e-02 1.40077010e+00
-7.08582515e-01 -1.02135439e+00 -7.95241554e-01 4.33486476e-01
1.17678609e+00 -1.22410972e+00 5.56655941e-01 -2.25422547e-01
4.12360789e-01 8.53548647e-01 5.84419888e-01 2.35966220e-01
9.34810095e-01 4.08929496e-01 1.41818981e+00 4.17499016e+00
1.74215975e+00 1.45340249e-01 -1.45457222e+00 -4.13887302e-01
-3.42933322e-02 8.06218006e-02 -7.03622133e-01 -1.35116142e+00
4.53227286e-01 -1.22784317e+00 2.83971598e-03 6.18261275e-01
1.57533343e+00 -8.96754271e-01 -6.60752714e-01 -1.48592563e-02
-1.33297717e+00 -8.84578788e-01 -8.81969266e-01 -1.02425463e+00
-1.23444938e+00 -7.09816316e-01 6.26337060e-01 -1.22405249e+00
2.41393570e-01 1.08893216e+00 -2.84178007e-01 7.68739164e-01
2.40478094e-02 5.96014097e-02 -8.70089071e-01 -4.40802009e-01]
Unique values in p90r_600: [-6.52492040e-01 -3.68825967e-01 -4.49829449e-01 -6.88846984e-01
-4.31625383e-01 -8.25659720e-01 6.41311739e-01 -5.83994900e-01
-8.02379880e-02 -4.32111156e-01 4.30305559e-01 3.97631140e-01
-6.93379917e-01 -2.35632061e-01 7.75718304e-01 8.81896867e-01
-7.33982713e-01 -9.62729706e-01 -3.37034449e-01 -6.68895910e-01
1.12591432e+00 -7.16393487e-01 4.66547038e-01 5.38742768e-02
-5.84824614e-01 -3.57291525e-01 3.05174770e-01 -5.85622416e-01
-6.47188963e-01 2.88576945e-01 -7.41474959e-01 3.46798752e-01
-5.94915921e-01 -6.18872670e-01 -6.57669597e-01 -5.61177767e-01
3.31211477e-01 -5.82250374e-01 7.63201680e-01 2.79089133e+00
2.90247011e-01 1.46534177e+00 -6.02535815e-01 2.91410740e+00
2.96235843e-01 2.65352047e-01 -4.45709264e-02 6.46694243e-01
-8.46737664e-02 -5.67436080e-01 -2.70164471e-01 -9.15118838e-01
-8.12483224e-01 -7.56224720e-01 3.50497007e-01 6.38733934e-02
-8.67821952e-01 -6.13678448e-01 3.91323187e-01 -5.54582605e-01
-5.12781334e-01 -9.27101112e-01 5.58741020e-01 5.22336435e-01
-5.80920704e-01 -6.47265906e-01 -8.58518519e-01 -5.89650429e-01
-6.76449853e-01 1.24118073e+00 1.37990959e-01 -8.01845512e-01
-7.73488797e-01 5.18638180e-01 -5.34846760e-01 2.14394849e+00
-7.25834497e-01 7.76324634e-01 -5.88356217e-01 -1.77332247e-01
-7.32164079e-01 -7.70741877e-01 -9.24894570e-01 -2.73610975e-01
-4.30238981e-01 -4.30572285e-01 1.04307057e+00 -1.81679380e-01
-3.47849097e-01 -7.71944253e-01 7.29601811e-01 -3.11976380e-01
1.00010274e+00 -7.35225156e-01 3.19652214e-01 3.34973556e-01
6.59820742e-01 1.47828744e+00 1.02187386e+00 -6.47597083e-01
-6.70552856e-01 3.16670919e+00 -7.87676905e-01 -3.51072216e-01
-4.27420081e-01 -7.02913472e-01 8.91945625e-01 -4.96782747e-01
-6.08801219e-01 -2.73486872e-01 -2.73050741e-01 2.17373309e+00
-5.76403372e-01 -9.29237448e-01 -6.28903699e-01 -6.28959013e-01
-2.93885779e-01 -3.04969906e-01 -6.13159700e-01 1.15287647e+00
-3.15554078e-01 -4.12775985e-01 2.77415522e+00 2.92967340e+00
-5.60894104e-01 1.54064007e-01 -3.44033831e-01 -7.01305104e-01
6.73542934e-01 8.74291156e-01 -9.41944482e-01 -9.16817624e-01
-5.13752898e-02 5.21198238e-01 8.71844564e-01 4.50534268e-01
1.80965887e+00 2.07116057e-01 -5.63181155e-02 -7.02169921e-01
-2.12814928e-01 -5.86788980e-01 -2.18509460e-01 7.79054889e-01
-7.02505352e-01 -7.01344107e-01 -5.66606366e-01 1.48125172e+00
5.16436247e-01 -7.24794163e-01 5.83479969e-01 7.63368313e-02
-3.44852908e-01 3.11522438e+00 -7.70706419e-01 -5.64954048e-02
-5.60766456e-01 4.18682453e-02 -2.73146477e-01 -6.83562345e-01
1.09912236e+00 5.76299753e-01 -2.73164206e-01 -8.03412395e-01
6.40602582e-01 7.34048227e-01 8.74393984e-01 6.50602410e+00
9.37693356e-01 1.15368137e+00 -5.87951998e-01 1.50629206e+00
5.66123347e-01 -5.30939304e-01 -1.88526293e-01 -1.87405825e-01
-3.16507894e-01 9.33236303e-01 -5.63021576e-01 -2.48435894e-01
-6.26812394e-01 -2.41450696e-01 -7.52920047e-01 -4.67203800e-01
-3.99184987e-01 -6.33222821e-01 9.69850089e-01 -5.89923455e-01
-9.19319176e-01 1.67818111e-01 -8.07843209e-01 -5.43225453e-01
2.64139388e-01 -4.86400686e-01 8.77280254e-01 -5.54674796e-01
-7.27332237e-01 -4.75036442e-01 -6.98810289e-01 -8.57679231e-01
-7.72659438e-01 2.08891789e+00 -6.23676146e-01 -5.55181843e-01
5.49710614e+00 -9.29925685e-01 6.43421482e-01 -4.69125616e-01
-7.86687631e-01 -7.57907904e-01 6.59611541e-01 2.62217572e-01
-5.76587753e-01 -9.27553555e-01 1.45120118e+00 -3.61702483e-01
-4.67377544e-01 -7.24478943e-01 -5.76460105e-01 -4.79443854e-01
-5.38509557e-01 -6.07507007e-01 -2.93754585e-01 -1.79420715e-01
-5.21626608e-04 -4.32075698e-01 -6.61575635e-01 9.13284146e-02
-1.65936091e-01 -8.35449280e-01 2.29465147e-01 2.35698638e-01
2.62483506e-01 -8.14914924e-01 3.65087916e-01 -6.06652473e-01
-5.56539879e-01 1.42806493e+00 -2.37465232e-01 2.41107028e+00
1.26916762e+00 -5.24581710e-01 6.38063799e-01 4.24094053e+00
6.41620223e-01 -4.12648336e-01 -7.41715363e-01 -6.23667282e-01
-4.53772363e-01 -1.11696220e-02 -3.47427148e-01 -9.20476520e-01
-2.73731531e-01 -8.00564065e-01 8.16200525e-02 3.66070099e-01
8.91747061e-01 -9.30918222e-01 -4.08070727e-01 -6.73361473e-01
-7.01463246e-01 -6.12434232e-01 -6.55853445e-01 -3.96355450e-01
-8.14681612e-01 -5.23315864e-01 -1.96291565e-01 -7.58357155e-01
-1.56054191e-03 6.94402794e-01 -5.35669383e-01 1.43322404e+00
-6.57735194e-01 1.65389247e-01 -4.74323757e-02 -6.17544064e-01]
Unique values in p00r_600: [-0.62200101 -0.36056015 -0.38658554 -0.62824953 -0.40878055 -0.75951772
0.52573835 -0.55335697 -0.12707955 -0.40389644 0.31418025 0.324763
-0.66535971 -0.24132784 0.6434476 0.73419885 -0.68045474 -0.88691384
-0.33580348 -0.62020755 0.89471752 -0.63057228 0.37992956 0.01721223
-0.5476553 -0.35391376 0.22180904 -0.52364351 -0.60603181 0.20710522
-0.66457153 0.27522846 -0.49006637 -0.57857995 -0.60850445 -0.52036422
0.25043242 -0.51561031 0.63662559 2.67245299 0.18504042 1.58574536
-0.56845745 3.47534913 0.13790403 0.32610439 -0.07493188 0.54049062
-0.11068916 -0.52907266 -0.24915211 -0.83754665 -0.73878007 -0.70011443
0.27825946 0.02236886 -0.78714218 -0.54131171 0.31915217 -0.5242158
-0.48486129 -0.85033346 0.45490206 0.42838916 -0.54620188 -0.60609328
-0.79397207 -0.55214578 -0.62959607 1.00879926 0.09109164 -0.74231916
-0.70477901 0.41400026 -0.50552718 2.24266314 -0.6493896 0.6457095
-0.55411093 -0.19341326 -0.68985052 -0.71336663 -0.84802494 -0.28719853
-0.42151922 -0.42174026 1.09960198 -0.2315475 -0.35972746 -0.71727756
0.60464116 -0.31194309 0.83734357 -0.66781963 0.25380861 0.23942879
0.54136873 1.59390876 0.85565672 -0.57418031 -0.62732903 2.97143461
-0.72762806 -0.35352618 -0.41144214 -0.62234529 0.74307988 -0.47425129
-0.58008485 -0.27602836 -0.27563775 2.07333611 -0.5370998 -0.85281125
-0.5912856 -0.59133314 -0.33274826 -0.32672261 -0.57514623 0.95805354
-0.31589459 -0.40637937 2.97927705 3.19941036 -0.56807895 0.36048394
-0.34765798 -0.65226495 0.47058693 0.72837304 -0.86780723 -0.84877466
-0.06968744 0.38077739 0.69711532 0.35113055 1.79038456 0.26964488
-0.1577226 -0.65295291 -0.10831221 -0.54904514 -0.26127004 0.64643924
-0.67481726 -0.67388102 -0.53028082 1.59663696 0.41201088 -0.69134361
0.48104857 0.14061709 -0.24084639 3.1412128 -0.71726666 -0.08588101
-0.49779072 0.06081801 -0.28679581 -0.63906331 0.8687103 0.47411755
-0.28682609 -0.74363179 0.53005926 0.60616423 0.72845782 7.07309053
0.78384845 0.95868941 -0.55374758 1.52419584 0.47465047 -0.48944564
-0.25857817 -0.25770309 -0.36535646 0.77934586 -0.49619195 -0.26560003
-0.59643648 -0.24653897 -0.71072685 -0.45400932 -0.40465343 -0.59187969
0.7591372 -0.55443795 -0.83673243 0.11663558 -0.74671547 -0.50661724
0.20429224 -0.46020151 0.73078633 -0.52430361 -0.67869549 -0.44408061
-0.65007028 -0.79364141 -0.71637159 2.02428302 -0.58222865 -0.52416432
5.94099365 -0.85344076 0.51967636 -0.45736128 -0.71721094 -0.7028072
0.46419792 0.20269953 -0.53726331 -0.84701511 1.4377867 -0.36313393
-0.43686496 -0.67650203 -0.54562051 -0.48012858 -0.47700977 -0.5452511
-0.30460329 -0.2148967 -0.02173047 -0.40385708 -0.61915594 0.05092563
-0.24507646 -0.75996011 0.08262846 0.17635923 0.20294177 -0.74725475
0.27541014 -0.55733269 -0.52340127 1.54633029 -0.25645859 2.67430005
1.04833242 -0.49015721 0.52250145 4.01114817 0.53394112 -0.40627642
-0.69776836 -0.58693562 -0.43679835 -0.04511245 -0.34792141 -0.84345483
-0.28729845 -0.7374944 0.0629285 0.27699679 0.74291031 -0.85482394
-0.38207387 -0.63 -0.67418412 -0.54026706 -0.57874043 -0.41589931
-0.74533411 -0.46377452 -0.20736311 -0.69868341 -0.02271759 0.57265975
-0.50954529 1.55329159 -0.61574735 0.14402355 -0.14418152 -0.57821659]
Unique values in p10r_600: [-5.99107008e-01 -3.17109910e-01 -3.39928183e-01 -5.84963231e-01
-3.67126617e-01 -7.14855461e-01 4.47150213e-01 -5.54806305e-01
-1.59155051e-01 -3.65305137e-01 2.14673421e-01 2.83938085e-01
-6.48341313e-01 -2.27819730e-01 5.63151844e-01 6.38739222e-01
-6.36007446e-01 -8.38389955e-01 -3.12710915e-01 -5.92269329e-01
7.31567432e-01 -5.71842388e-01 3.21427745e-01 8.55362395e-04
-5.06081046e-01 -3.34124738e-01 1.57462272e-01 -4.82404498e-01
-5.63321790e-01 1.44674246e-01 -6.20292676e-01 2.38471042e-01
-4.27329620e-01 -5.36357431e-01 -5.65581824e-01 -4.79286189e-01
2.05418043e-01 -4.74394830e-01 5.55370869e-01 2.54003864e+00
9.60619889e-02 1.57962908e+00 -5.34697382e-01 3.95272137e+00
1.56478236e-02 3.14324781e-01 -7.52432140e-02 4.68561346e-01
-1.06028107e-01 -4.87833961e-01 -1.98511930e-01 -7.89732543e-01
-6.93110705e-01 -6.55293070e-01 2.40790267e-01 1.22658440e-02
-7.40357256e-01 -4.99607662e-01 2.79218918e-01 -4.83227796e-01
-4.44632333e-01 -8.02243177e-01 3.82795742e-01 3.64177366e-01
-5.04622786e-01 -5.63380981e-01 -7.49707340e-01 -5.10474660e-01
-5.86344811e-01 8.42096551e-01 6.78788257e-02 -6.96607300e-01
-6.59495388e-01 3.39134036e-01 -4.64862329e-01 2.19107861e+00
-6.05427032e-01 5.65780479e-01 -5.12414522e-01 -1.84580435e-01
-6.57759736e-01 -6.68268894e-01 -8.00026460e-01 -3.04190048e-01
-4.23856163e-01 -4.24049880e-01 1.04907801e+00 -2.36902914e-01
-3.60739330e-01 -6.72219649e-01 5.28925780e-01 -2.89537494e-01
7.24868045e-01 -6.23590980e-01 2.11894117e-01 1.64635190e-01
4.49902612e-01 1.51798665e+00 7.43790449e-01 -5.31794315e-01
-5.84081010e-01 2.81578970e+00 -6.82195547e-01 -3.63332988e-01
-3.89253426e-01 -5.78928671e-01 6.43751655e-01 -4.46480718e-01
-5.65135198e-01 -2.59968715e-01 -2.59602804e-01 1.96346089e+00
-4.95684889e-01 -8.04723834e-01 -5.56019728e-01 -5.56062776e-01
-3.66168793e-01 -3.33484395e-01 -5.32967380e-01 8.23957087e-01
-2.73617706e-01 -4.10376674e-01 3.15901893e+00 3.39115671e+00
-5.68256198e-01 5.04611580e-01 -3.58110695e-01 -6.08432071e-01
3.10159861e-01 6.35368004e-01 -8.18919135e-01 -8.04090217e-01
-8.99549597e-02 2.70165329e-01 5.81824030e-01 2.70969794e-01
1.90316641e+00 2.60743139e-01 -2.29256466e-01 -6.09209092e-01
-6.97949175e-02 -5.07434376e-01 -2.59148107e-01 5.65863885e-01
-6.55465532e-01 -6.54693892e-01 -4.89028550e-01 1.52057493e+00
3.37339461e-01 -6.67054664e-01 4.20411857e-01 1.38262744e-01
-2.07858786e-01 3.31348149e+00 -6.72118486e-01 -8.60025906e-02
-4.56927995e-01 1.05828565e-01 -3.03799923e-01 -5.95549876e-01
7.03066787e-01 4.03542317e-01 -3.03837591e-01 -6.97888525e-01
4.63438602e-01 5.20289221e-01 6.35435267e-01 7.45050080e+00
6.83652018e-01 8.24473666e-01 -5.12059374e-01 1.45143941e+00
4.17234357e-01 -4.48964065e-01 -3.11282250e-01 -3.10566573e-01
-3.98511495e-01 6.78852136e-01 -4.55464354e-01 -2.84560038e-01
-5.79784524e-01 -2.32592706e-01 -6.78800653e-01 -4.52792671e-01
-4.08296904e-01 -5.49384913e-01 6.06065586e-01 -5.12664740e-01
-7.88906016e-01 9.32450178e-02 -7.00921813e-01 -4.65852439e-01
1.71286147e-01 -4.20509160e-01 6.37063030e-01 -4.83321964e-01
-6.34334483e-01 -4.04610896e-01 -6.06283424e-01 -7.46713601e-01
-6.71245413e-01 1.92495960e+00 -5.39927747e-01 -4.83093270e-01
6.23105098e+00 -8.05358257e-01 4.17261262e-01 -4.50729044e-01
-6.71914814e-01 -6.58175690e-01 3.08545551e-01 1.74541673e-01
-4.95843629e-01 -7.98957518e-01 1.36910421e+00 -3.27594854e-01
-3.97583266e-01 -6.32219467e-01 -5.13286250e-01 -4.71061279e-01
-4.36692618e-01 -5.03409363e-01 -3.19757378e-01 -2.32947855e-01
-4.56959588e-02 -3.65270160e-01 -5.76066768e-01 2.78708413e-02
-3.00291489e-01 -7.13715759e-01 -3.52056339e-02 1.50353927e-01
1.74756914e-01 -7.09499181e-01 2.05084419e-01 -5.15355257e-01
-4.82323783e-01 1.47349896e+00 -2.76189840e-01 2.84436299e+00
8.90372494e-01 -4.49752387e-01 4.37991694e-01 3.81085042e+00
4.59591163e-01 -4.10285196e-01 -6.70376914e-01 -5.52753440e-01
-4.10933611e-01 -4.89084358e-02 -3.06781016e-01 -7.95531414e-01
-3.04281526e-01 -7.02051830e-01 3.66150208e-02 2.09965016e-01
6.43574081e-01 -8.06705399e-01 -3.38300420e-01 -5.86726596e-01
-6.54979356e-01 -4.98585266e-01 -5.36276716e-01 -4.43128334e-01
-6.99456827e-01 -4.23743161e-01 -1.96141585e-01 -6.53893194e-01
-4.66080440e-02 4.79675870e-01 -4.79245831e-01 1.48341889e+00
-5.72764428e-01 1.20416547e-01 -2.23552570e-01 -5.35978068e-01]
Unique values in p90_300: [-1.17244295e+00 -5.86884803e-01 4.14370244e-01 -1.14533496e+00
-7.41186312e-01 -5.77644174e-01 1.89403349e+00 -1.00938375e+00
-7.44687734e-01 -4.82154607e-01 -2.76365653e-01 1.25613953e-02
-9.60319728e-01 8.13307192e-01 9.78384074e-01 1.68625029e+00
-1.19761045e+00 -1.40115547e+00 -7.84646219e-01 -1.39060901e+00
3.54749575e-01 -1.07169206e+00 1.77555033e+00 1.47731373e+00
-4.47751528e-01 -1.01089046e+00 9.00016374e-02 -8.47533963e-01
-6.45292382e-01 3.31012328e-02 -1.10025760e+00 -8.45777917e-02
-1.02794128e+00 -5.72993992e-01 -1.00671219e+00 -2.94451738e-01
3.16233933e-01 -8.02516337e-01 2.04272445e+00 2.32653722e+00
-5.91337399e-01 -4.91294146e-01 -8.90533626e-02 1.82285170e+00
-6.23461337e-01 -4.06400005e-02 -1.58277670e-01 1.94658699e+00
-3.89927520e-01 -4.98673783e-01 -7.67865126e-01 -1.12316480e+00
-1.02037463e+00 -1.13492948e+00 8.60499013e-02 -3.94885570e-01
-1.02562952e+00 -7.64928894e-01 -6.76920587e-04 -7.53942149e-01
-2.32570308e-01 -6.84125081e-01 1.37821246e+00 1.45838216e+00
-1.84639425e-01 -6.44938563e-01 -1.27266311e+00 -4.44893412e-01
-1.04226587e+00 4.52656134e-01 1.58296753e+00 -1.13895796e+00
-1.23910506e+00 1.39731864e+00 -3.41082224e-01 1.05428498e+00
-1.10034031e+00 7.26934188e-01 -6.34788116e-01 2.32576599e-01
-1.18106049e+00 -1.18634938e+00 -1.25668937e+00 9.12734710e-01
9.24727769e-01 9.43130913e-01 8.19404813e-01 -5.47597195e-01
3.05188193e-02 -1.01728079e+00 9.01132229e-01 -7.60251141e-01
1.58567401e+00 -1.07932902e+00 1.66838017e+00 -2.71131900e-01
1.54542604e+00 1.57280789e+00 7.27816436e-01 -8.86453969e-01
4.05060689e-01 2.58175578e-01 -1.15614433e+00 2.15554652e+00
-1.67136170e-02 -9.98658460e-01 1.81954327e+00 3.09097833e-01
-9.69692694e-01 6.49066607e-01 6.51093021e-01 7.99177438e-01
4.91828867e-01 -1.32831045e+00 -6.32844413e-01 -6.32270033e-01
-8.15612207e-01 -7.38024183e-02 6.13602074e-01 4.67190252e-01
-7.00419100e-01 1.02209671e+00 2.28330781e-01 2.01041671e+00
-6.16394163e-01 -5.14250975e-01 1.46127244e+00 -7.34546477e-01
-3.62421599e-01 1.36594829e+00 -1.22356141e+00 -1.35127003e+00
2.92725699e-01 -1.37815948e-01 -3.18401097e-01 3.69421544e-01
3.86358869e-01 -1.15125631e-01 -6.67169376e-01 -8.50672377e-01
-7.30212612e-02 -4.86285550e-01 -5.61685593e-01 9.77285859e-01
-9.30120653e-01 -9.30111462e-01 5.34833864e-01 1.57473321e+00
1.39113831e+00 -9.17300485e-01 4.91718586e-01 -3.07460302e-01
-9.23255660e-01 8.08064249e-01 -9.31315363e-01 -4.62124819e-01
-8.06624305e-01 -5.86590721e-01 8.73051928e-01 3.18361438e-01
2.82515515e-01 1.47053145e+00 8.89663004e-01 -1.13470938e+00
6.69574280e-01 2.04813282e+00 1.36886614e+00 3.90364293e+00
1.10403550e+00 4.66193127e-01 -6.36782364e-01 8.86754343e-01
4.44449389e-01 -5.04968990e-01 -7.38470643e-01 -7.34771634e-01
-1.09032605e-01 1.48907244e+00 -7.57627372e-01 7.88480180e-01
-9.88954191e-01 8.09180844e-01 -1.10813074e+00 -6.19353370e-01
-1.09510701e+00 4.69749690e-01 -9.75672350e-03 -1.73592945e-01
-1.22079244e+00 1.06282257e+00 -1.23373529e+00 4.83787543e-01
1.12166667e+00 -1.31015286e-01 1.44481300e+00 -7.85399806e-01
-5.31551308e-01 -2.72730975e-01 -7.01475960e-01 -1.30574879e+00
-1.09735353e+00 2.90223624e+00 -6.33947223e-01 -6.41947191e-01
1.15465907e+00 -8.89201804e-01 2.62807380e-01 -9.17879461e-01
-1.10736612e+00 -1.16583895e+00 -5.52187642e-01 -8.63790482e-02
4.91962123e-01 -4.56174240e-01 1.37556112e+00 -7.42233982e-01
-1.34613204e-01 -6.58470962e-01 6.99167090e-02 -7.24138707e-01
-7.76434879e-01 -8.48462162e-01 1.11481087e+00 2.18906349e-01
5.13113101e-01 -4.82145417e-01 4.69997822e-01 1.41982976e+00
-8.72742364e-01 -1.04640232e+00 -3.82341106e-01 -3.07984137e-01
-8.63468829e-02 -9.09001840e-01 3.23314893e-01 -7.11392060e-01
6.93413357e-01 1.43335756e+00 7.86963817e-01 1.07737966e+00
3.84847100e-01 5.40798229e-01 1.86506175e+00 3.49486799e+00
2.01980438e+00 1.02163720e+00 -1.09558536e+00 -5.24713886e-01
5.50521338e-01 -4.32780881e-01 -6.57492218e-01 -1.08969819e+00
9.18588793e-01 -1.11585638e+00 4.87743874e-01 5.87929574e-01
1.81887239e+00 -8.88581473e-01 -7.76467044e-01 1.55127167e-01
-9.88362350e-01 -7.62695704e-01 -8.84592977e-01 -8.86380448e-01
-1.14727039e+00 -7.52866909e-01 5.10213629e-01 -1.10032974e+00
5.04580108e-01 1.70806755e+00 2.80250160e-01 1.72711400e+00
2.45594353e-01 5.66911852e-01 -4.55103595e-01 -4.97451502e-01]
Unique values in p00_300: [-1.13629567 -0.60026057 0.4963653 -1.09499068 -0.72815525 -0.53548603
1.75206746 -0.99121079 -0.74630006 -0.49815412 -0.40192085 -0.04682929
-0.9617266 0.69932085 0.89333842 1.56286011 -1.15810295 -1.35100918
-0.77526889 -1.33853627 0.2523554 -1.02059322 1.60797192 1.31647613
-0.41731933 -0.98237207 0.0420956 -0.7696232 -0.60174955 -0.00719774
-1.02500142 -0.12060799 -0.9435061 -0.54000672 -0.97736787 -0.28037086
0.21980476 -0.71251274 1.8807728 2.42394671 -0.66912566 -0.37755543
-0.11618656 2.3394846 -0.68088443 0.05706394 -0.19320793 1.78303401
-0.41039146 -0.46897849 -0.74285474 -1.04416494 -0.92509286 -1.09760756
0.03598253 -0.40260743 -0.91976977 -0.65352452 -0.06004394 -0.71278158
-0.25408218 -0.62960992 1.26613223 1.32529831 -0.16578597 -0.60141039
-1.23322174 -0.41467226 -1.02087323 0.33721456 1.40131047 -1.09396991
-1.18856241 1.28680003 -0.35107649 1.22832882 -1.02207558 0.6637509
-0.60921097 0.15293324 -1.14416615 -1.1471168 -1.17354197 0.78371678
0.82946139 0.846779 0.9543078 -0.58009324 -0.09142408 -0.98726376
0.81749583 -0.74745815 1.4378979 -1.04350193 1.49073582 -0.3265084
1.38813305 2.16868264 0.66818887 -0.79589947 0.34015115 0.26269551
-1.11786506 1.97354007 -0.0520986 -0.88974211 1.67437606 0.25345559
-0.96166373 0.54640727 0.54828089 0.788436 0.44904072 -1.27538413
-0.62900606 -0.62847251 -0.84972177 -0.14793068 0.5342349 0.37766505
-0.69305266 0.92269604 0.44789503 2.53358903 -0.67526355 -0.31146976
1.32964942 -0.69060413 -0.44529551 1.26741854 -1.19234358 -1.3119208
0.16058492 -0.2563446 -0.37987575 0.27598047 0.44554576 -0.0199657
-0.7334742 -0.82294918 0.04296417 -0.45466365 -0.59260063 0.89313161
-0.95946253 -0.95949355 0.47155319 2.17051491 1.28131978 -0.93994083
0.41785083 -0.21900855 -0.85419284 0.95211984 -0.91179548 -0.46294814
-0.72164925 -0.61882313 0.74621115 0.25932463 0.19289567 1.3462184
0.76194879 -1.09000014 0.59130399 1.90226781 1.27008629 4.98030153
1.0221182 0.37662277 -0.61104323 1.00386585 0.35151286 -0.46559107
-0.78440955 -0.78148123 -0.25407805 1.37722217 -0.64866053 0.66546322
-0.97943465 0.69554051 -1.07848457 -0.63196747 -1.06338471 0.41076165
-0.10441125 -0.15126433 -1.09435001 0.91384905 -1.18958526 0.43397725
0.96842411 -0.13706944 1.33931535 -0.74196549 -0.54293918 -0.28639294
-0.65784254 -1.26354099 -1.05642582 3.00525905 -0.59860616 -0.61340491
1.33529925 -0.78529879 0.14277512 -0.89945354 -1.06930835 -1.11998064
-0.60467787 -0.132222 0.44948741 -0.39267679 1.47996144 -0.74589473
-0.16733285 -0.66172629 0.0349568 -0.73744066 -0.68659217 -0.75619761
0.9850055 0.12576358 0.41626259 -0.49815826 0.4012198 1.2724521
-0.9110634 -0.94562458 -0.48265224 -0.32693855 -0.13220132 -0.79460489
0.24979519 -0.65264767 0.61489184 1.96673628 0.66376744 1.53962383
0.27940511 0.47732297 1.71771764 3.43147811 1.857764 0.92224521
-1.07395354 -0.53030771 0.47206606 -0.43598528 -0.65996433 -1.00689631
0.78923012 -1.03073852 0.51680975 0.52232723 1.67361503 -0.78562968
-0.7607638 0.10361508 -1.01000124 -0.65149372 -0.77396604 -0.89370857
-1.10862845 -0.66551904 0.41245743 -1.06026696 0.4060052 1.54605538
0.22933833 2.2514986 0.18803582 0.57058243 -0.55169931 -0.46491276]
Unique values in p10_300: [-1.12515125 -0.55610764 0.60507609 -1.07117365 -0.6858375 -0.50278478
1.63350571 -1.01174234 -0.7587987 -0.4556458 -0.48769443 -0.04247873
-0.98663016 0.67985494 0.82643866 1.41935573 -1.13658388 -1.33540196
-0.758586 -1.32312114 0.17053425 -0.99439152 1.54055424 1.28631157
-0.37115607 -0.97082435 -0.02086031 -0.73504551 -0.56156446 -0.06665733
-0.99881266 -0.1187001 -0.87964915 -0.49772244 -0.95001537 -0.23007944
0.21010872 -0.67667964 1.77291165 2.43500767 -0.73166546 -0.34586754
-0.11215657 2.9858249 -0.74985741 0.08484564 -0.18776303 1.69592068
-0.40291851 -0.42458334 -0.69446553 -1.01840305 -0.89591904 -1.07367427
0.03535144 -0.39578714 -0.89075614 -0.61547902 -0.05578624 -0.67736803
-0.20325945 -0.59039546 1.17552393 1.25491652 -0.11115106 -0.56121253
-1.21959938 -0.36838705 -0.99499715 0.25718196 1.37447141 -1.07010511
-1.16816533 1.17372175 -0.30344284 1.29593737 -0.99600691 0.60236122
-0.57096982 0.14625897 -1.13277378 -1.12482949 -1.15197627 0.66519773
0.70833015 0.72456137 0.98072998 -0.577378 -0.1346374 -0.95962609
0.76135136 -0.72774011 1.27704542 -1.01793704 1.45833077 -0.37570405
1.23972174 2.1936819 0.5784572 -0.76252295 0.41131859 0.27655346
-1.09453354 1.78054964 -0.05950276 -0.85942684 1.51380773 0.25175222
-0.9703243 0.53048287 0.53228505 0.80085622 0.52419458 -1.25754686
-0.61475969 -0.61426854 -0.89125116 -0.20789252 0.61122903 0.30070498
-0.64207083 0.79563144 0.62176752 2.89374358 -0.7298014 -0.12319395
1.17702833 -0.65329385 -0.5451244 1.14300735 -1.16802302 -1.30020627
0.1243737 -0.35436022 -0.40851068 0.19330127 0.6005281 0.00817953
-0.78949376 -0.79008547 0.11364957 -0.40964381 -0.5894789 0.82558011
-0.97774186 -0.97779716 0.5469616 2.19551115 1.16861687 -0.95552942
0.39420175 -0.19044696 -0.83014335 1.17118478 -0.88203916 -0.4548646
-0.68618943 -0.62332971 0.63004749 0.32799292 0.10768227 1.2575347
0.64479365 -1.06597711 0.55439849 1.75969695 1.14550952 5.56301901
0.90841076 0.29983096 -0.57286482 1.02400936 0.34562411 -0.42162096
-0.8328853 -0.83035606 -0.35313427 1.24012782 -0.61055976 0.55439076
-0.98696662 0.67625445 -1.0717495 -0.66146553 -1.05380312 0.48458917
-0.17790131 -0.09611485 -1.0699713 0.89800375 -1.16867273 0.50843131
0.95125313 -0.08214215 1.21017141 -0.70736697 -0.50120304 -0.23610862
-0.61942757 -1.24492078 -1.03138803 3.01591279 -0.55815733 -0.57532058
1.58830813 -0.75222036 0.06246535 -0.8952964 -1.0445304 -1.09708521
-0.67431283 -0.12725465 0.52466253 -0.3446416 1.49235561 -0.70101293
-0.11419852 -0.62445511 0.03865415 -0.76028376 -0.649558 -0.72162198
0.85397797 0.04873243 0.37719319 -0.45564967 0.47445675 1.2419648
-0.94296134 -0.91674852 -0.58994298 -0.32119006 -0.12723145 -0.7606937
0.17143147 -0.61446964 0.69406741 1.99203889 0.55280902 1.81199884
0.20863526 0.55284382 1.58029501 3.44147467 1.75905884 0.7952099
-1.07563115 -0.52902081 0.47049273 -0.42863244 -0.60756644 -0.97992072
0.67036449 -1.00571277 0.48917584 0.43737284 1.51298785 -0.75253748
-0.71847783 0.16670172 -1.02550697 -0.61339065 -0.73968632 -0.92829253
-1.08493983 -0.6278313 0.398742 -1.03519349 0.36709171 1.38862586
0.23508012 2.27646227 0.25367815 0.54161694 -0.64098024 -0.42029833]
Unique values in p90u_300: [-1.19151445e+00 -7.16400905e-01 6.53952122e-01 -1.16935750e+00
-7.01982421e-01 -4.13600183e-01 2.07373277e+00 -1.01856618e+00
-8.41039077e-01 -3.90784535e-01 -5.59167783e-01 -8.75809320e-04
-9.47131208e-01 1.17125135e+00 8.57363359e-01 1.61253614e+00
-1.21179837e+00 -1.40690416e+00 -8.82244890e-01 -1.40272025e+00
-5.74435297e-02 -1.02360260e+00 2.27707486e+00 1.93974269e+00
-2.82513919e-01 -1.08214767e+00 4.28761797e-02 -8.43147167e-01
-4.89664911e-01 -2.26543817e-02 -1.09967235e+00 -1.48027306e-01
-1.07730925e+00 -4.30884764e-01 -9.95648713e-01 -1.01629205e-01
2.86852758e-01 -8.36885749e-01 2.21863412e+00 1.58312093e+00
-7.71303020e-01 -8.72281429e-01 1.52271866e-01 -3.52187009e-02
-8.90934320e-01 7.56163192e-02 -1.68781374e-01 2.32496887e+00
-4.65554491e-01 -3.38823942e-01 -7.79015714e-01 -1.06298441e+00
-9.76852517e-01 -1.12959856e+00 7.70996506e-02 -4.26327920e-01
-9.43181524e-01 -7.52937367e-01 -1.53634310e-02 -6.60970824e-01
-7.24779727e-02 -4.46780293e-01 1.64738186e+00 1.77699107e+00
3.57800735e-02 -4.89206084e-01 -1.25910344e+00 -2.78397046e-01
-1.05525098e+00 1.11687669e-01 2.06075362e+00 -1.14961473e+00
-1.23106282e+00 1.61931798e+00 -2.06141211e-01 -2.15135478e-01
-1.09124565e+00 5.38748817e-01 -5.65999907e-01 3.74400733e-01
-1.20444331e+00 -1.19652132e+00 -1.22657512e+00 1.16939719e+00
1.23593969e+00 1.25969813e+00 8.12184606e-01 -5.16691710e-01
8.97645346e-02 -9.67093328e-01 7.65264825e-01 -8.58065332e-01
1.43370672e+00 -1.08394715e+00 2.15974084e+00 -4.01054719e-01
1.58352947e+00 1.41221099e+00 3.87335885e-01 -9.00013440e-01
8.71021321e-01 -1.36399497e-01 -1.14906163e+00 2.87725838e+00
2.05891779e-01 -9.66784091e-01 1.76430733e+00 5.52959885e-01
-1.05685939e+00 9.95564585e-01 9.97789582e-01 5.09855282e-01
9.58041331e-01 -1.32447876e+00 -5.03115457e-01 -5.02304653e-01
-9.02533217e-01 -1.02961689e-01 1.08973727e+00 1.98701394e-01
-7.54024724e-01 1.32809479e+00 -7.99834521e-01 8.18796744e-01
-4.79419868e-01 -7.01460741e-01 1.83677058e+00 -6.29494030e-01
-8.03811232e-01 1.26099290e+00 -1.18985261e+00 -1.35785227e+00
3.71987177e-01 -4.91273948e-01 -5.94202058e-01 3.17707307e-01
-5.39318798e-01 1.43283369e-02 -8.78091562e-01 -8.07677321e-01
-1.72081158e-01 -3.25040274e-01 -5.41367807e-01 8.58035886e-01
-8.76209114e-01 -8.76260025e-01 9.79084523e-01 1.41355604e+00
1.61412632e+00 -8.67554253e-01 4.00007054e-01 -1.52194461e-01
-8.20889026e-01 -1.53225251e-01 -8.73734591e-01 -4.67735491e-01
-8.49257738e-01 -8.67118682e-01 1.11470878e+00 7.72354646e-01
-1.83526693e-01 1.71383636e+00 1.13746157e+00 -1.14202523e+00
5.43789629e-01 2.11336160e+00 1.26438068e+00 8.57696480e-01
8.63705229e-01 1.98236281e-01 -5.68520313e-01 5.74656749e-01
5.06480075e-01 -4.17610205e-01 -8.86128578e-01 -8.82378767e-01
7.85829819e-02 1.36634085e+00 -7.68625481e-01 1.02119605e+00
-1.06915344e+00 1.16935319e+00 -1.11054530e+00 -7.85234392e-01
-1.11469548e+00 9.44848481e-01 -4.33618870e-01 5.34103463e-02
-1.17910474e+00 1.37573109e+00 -1.25353718e+00 9.15320131e-01
1.46022441e+00 8.26307166e-02 1.34400917e+00 -7.01209329e-01
-3.43789330e-01 -1.24997958e-01 -5.86420854e-01 -1.31813689e+00
-1.11235232e+00 2.39865775e+00 -4.99463697e-01 -5.59764887e-01
-4.77867398e-01 -7.46130384e-01 1.02479701e-01 -9.61711852e-01
-1.09637508e+00 -1.14795604e+00 -9.59398861e-01 -1.25708198e-01
9.58481302e-01 -1.39818701e-01 1.15369022e+00 -7.13101121e-01
1.63710601e-02 -5.46238916e-01 3.08285639e-01 -7.70875619e-01
-7.87786225e-01 -8.55018846e-01 1.50877209e+00 3.89208905e-01
7.13436223e-01 -3.90797106e-01 9.50712668e-01 1.88877518e+00
-9.99634223e-01 -9.71689770e-01 -5.81323474e-01 -3.81237161e-01
-1.25727054e-01 -7.57871329e-01 3.16399964e-01 -6.25961690e-01
1.16113830e+00 1.07323835e+00 1.02384845e+00 3.99950487e-01
1.14622905e-01 9.63013005e-01 2.00348194e+00 2.55123975e+00
2.38778418e+00 1.32732169e+00 -1.13454509e+00 -3.43311647e-01
8.12668575e-01 -4.47257976e-01 -6.76577229e-01 -1.02121795e+00
1.17739838e+00 -1.03033478e+00 7.49670990e-01 6.70306478e-01
1.76279258e+00 -7.43968240e-01 -7.29380054e-01 5.15556051e-01
-9.38849694e-01 -7.51196338e-01 -8.59599575e-01 -9.20808362e-01
-1.12878776e+00 -7.65822236e-01 7.43838230e-01 -1.09529087e+00
7.00255944e-01 1.71123424e+00 4.84167252e-01 1.19619772e+00
6.20325755e-01 8.67853529e-01 -5.37093801e-01 -3.60175113e-01]
Unique values in p00u_300: [-1.19804562 -0.73602362 0.77950701 -1.16242274 -0.7148587 -0.38126612
2.01089484 -1.03237611 -0.86252444 -0.42272146 -0.66838098 -0.05469897
-0.9847137 1.08257532 0.81573316 1.56879516 -1.21772509 -1.41052369
-0.89886227 -1.40150956 -0.12912478 -1.01115566 2.16884583 1.82858825
-0.25189545 -1.0905873 0.010722 -0.78765962 -0.45975711 -0.04890255
-1.06315032 -0.17987448 -1.03419303 -0.4035655 -1.0038283 -0.09080104
0.205555 -0.7753341 2.13692711 1.74364499 -0.85380204 -0.80759553
0.1224257 0.23098598 -0.94149994 0.18623951 -0.20648129 2.23645892
-0.49590645 -0.31222904 -0.77822936 -1.01295663 -0.90698907 -1.13478368
0.03560938 -0.44192469 -0.85469543 -0.66025063 -0.070227 -0.63806942
-0.10228162 -0.40169836 1.59050958 1.69927076 0.06476284 -0.45929623
-1.26889726 -0.24789527 -1.07359215 0.02356748 1.92910681 -1.14646456
-1.22633877 1.56990008 -0.2272326 -0.08069719 -1.05004308 0.50978732
-0.5545147 0.29768323 -1.21025532 -1.2018969 -1.17884889 1.0743327
1.18441742 1.20754402 0.98739821 -0.57076949 -0.03365814 -0.97547783
0.72225184 -0.8671084 1.36116394 -1.08964841 2.03552815 -0.45361798
1.49956899 2.05639172 0.37037779 -0.83954202 0.81848661 -0.12409649
-1.15414172 2.77453339 0.17084738 -0.88243021 1.70312913 0.51075044
-1.08000307 0.91137115 0.91352191 0.53221078 0.93978602 -1.32120803
-0.52408497 -0.52328729 -0.95849863 -0.17311494 1.03182561 0.13335086
-0.76448576 1.27552936 -0.71579228 1.26381834 -0.5750592 -0.53768676
1.7693714 -0.59869985 -0.8584374 1.22663498 -1.20715622 -1.37083414
0.2534449 -0.59061677 -0.63868984 0.25091007 -0.49357842 0.12119669
-0.94116432 -0.80696921 -0.05139602 -0.2947216 -0.5937011 0.81707443
-0.95055263 -0.95060877 0.93792478 2.05769754 1.56514359 -0.93534604
0.34902971 -0.05812601 -0.77724261 -0.05065743 -0.89006187 -0.48052023
-0.79293017 -0.9154125 1.02051048 0.72212776 -0.23523296 1.64901738
1.04292213 -1.1391567 0.49612644 2.05789253 1.22988476 1.54003758
0.83891884 0.13278954 -0.55694317 0.71403877 0.43308076 -0.38788385
-0.94640414 -0.94330445 -0.0839706 1.32571183 -0.67950113 0.9273955
-1.09159946 1.08076135 -1.12144128 -0.81210385 -1.12283159 0.90418618
-0.49050591 0.08765308 -1.07114064 1.25730697 -1.25590938 0.88825637
1.33952633 0.08160259 1.30627816 -0.67716129 -0.37892038 -0.14754806
-0.55403019 -1.3253518 -1.11109399 2.61265903 -0.47228352 -0.54476537
-0.41384071 -0.64574481 0.01151967 -0.97504532 -1.10010088 -1.14455783
-0.99933711 -0.17006015 0.94066641 -0.0726082 1.31178505 -0.74089237
-0.01813602 -0.57673136 0.27704419 -0.80662059 -0.71923704 -0.78729328
1.41983719 0.30220337 0.65377017 -0.4227451 0.89717257 1.78921868
-1.05385005 -0.89114612 -0.670839 -0.4036955 -0.17008379 -0.64453353
0.26566997 -0.58668158 1.11084247 1.62083886 0.92977079 0.78583521
0.03416766 0.92235539 1.94040422 2.62578222 2.30324479 1.27477305
-1.15188224 -0.36988009 0.75443645 -0.46044251 -0.6976467 -0.96444927
1.08219716 -0.96775695 0.8403842 0.63889801 1.70149833 -0.64443899
-0.7419973 0.46706161 -1.00718857 -0.65869665 -0.77151709 -0.96195403
-1.13375912 -0.6992775 0.66061834 -1.09667207 0.63780491 1.62962508
0.44685982 1.74669978 0.5693646 0.94167089 -0.64364722 -0.33008509]
Unique values in p10u_300: [-1.21575145 -0.70899805 0.93526138 -1.16641827 -0.68279415 -0.34959293
1.93721006 -1.07953771 -0.89169235 -0.38227541 -0.74830107 -0.04821113
-1.03669731 1.08841936 0.7756305 1.46423955 -1.22539039 -1.42952302
-0.90053978 -1.42047349 -0.18923526 -1.00952815 2.14351966 1.84181423
-0.19963165 -1.10469175 -0.05089114 -0.76845224 -0.42023842 -0.10793786
-1.06105814 -0.17907167 -0.98821924 -0.3604833 -0.99830731 -0.02924098
0.20478855 -0.7561083 2.07981267 1.8082403 -0.92164031 -0.80430304
0.13059431 0.54070385 -1.00790481 0.22711438 -0.2031009 2.19530857
-0.49777131 -0.26367933 -0.74489428 -1.00756016 -0.89554827 -1.13684448
0.03893459 -0.44331943 -0.84068757 -0.63363983 -0.06425712 -0.61083136
-0.04173255 -0.3590127 1.52987706 1.66188454 0.1368628 -0.41975579
-1.28657069 -0.19535613 -1.07256912 -0.03805889 1.9496051 -1.1493633
-1.23478462 1.48682657 -0.17437029 -0.04375959 -1.04733331 0.47083056
-0.52258979 0.2988898 -1.22787451 -1.20811626 -1.18364017 0.96388411
1.07006811 1.09234285 1.04922423 -0.58104465 -0.07768556 -0.96762632
0.69255589 -0.8659705 1.23724504 -1.0891301 2.05195079 -0.50750906
1.38318062 2.14596688 0.30541948 -0.82402836 0.93685122 -0.10893151
-1.15732781 2.60175581 0.16688799 -0.86953742 1.58371572 0.52303963
-1.11091085 0.91629123 0.9184148 0.5642902 1.06612191 -1.33523727
-0.5216586 -0.52087504 -1.01720024 -0.2376628 1.16276123 0.0714297
-0.73002363 1.1577646 -0.65272922 1.56421184 -0.6592078 -0.37980549
1.63344919 -0.56756511 -0.93391214 1.13384325 -1.20923539 -1.39296824
0.22276505 -0.67412387 -0.66819605 0.17572294 -0.41931291 0.16072738
-1.00177032 -0.7889157 0.02272394 -0.24499308 -0.60397235 0.77636863
-0.99809893 -0.99815685 1.06375987 2.14730688 1.48227851 -0.98022747
0.3399757 -0.02307469 -0.76790715 0.0919613 -0.87752123 -0.48177643
-0.77485133 -0.9392432 0.9120441 0.83472129 -0.29712266 1.59179549
0.9336318 -1.14157368 0.47936457 1.96423159 1.13698885 1.8718678
0.75580297 0.07103224 -0.52516759 0.76069739 0.44142995 -0.34480638
-1.00608331 -1.00332552 -0.20769439 1.22445822 -0.65414871 0.82238303
-1.12207207 1.08665919 -1.14231408 -0.85316211 -1.14022686 1.02819865
-0.54895835 0.16122704 -1.06903571 1.27357847 -1.26544404 1.01130096
1.35624426 0.15385134 1.21051309 -0.65216142 -0.33509703 -0.08908695
-0.52009147 -1.33910909 -1.1118869 2.70049597 -0.4332694 -0.51232399
-0.3144973 -0.61938241 -0.05966931 -0.99315624 -1.10020842 -1.14762811
-1.05405491 -0.16587603 1.06705878 -0.00829489 1.36503378 -0.70719245
0.0470314 -0.545773 0.28799942 -0.84777937 -0.69610903 -0.76860554
1.29679007 0.22034055 0.6278155 -0.38229812 1.02044252 1.80085324
-1.10169832 -0.8783752 -0.77575413 -0.40486811 -0.16589874 -0.61665697
0.19174621 -0.55551643 1.24623329 1.69888797 0.82468261 1.02945916
-0.02240469 1.04715744 1.84710611 2.71368594 2.25277546 1.15703782
-1.1801766 -0.37879481 0.77138904 -0.46191484 -0.65806084 -0.95610171
0.97145854 -0.96073324 0.8303606 0.56424477 1.58200097 -0.6179913
-0.71072416 0.56355206 -1.05284891 -0.63199889 -0.75157727 -1.01855898
-1.13572933 -0.67491311 0.66315528 -1.09651489 0.61171273 1.50970318
0.46278485 1.82805079 0.67189938 0.93192273 -0.74435487 -0.28257566]
Unique values in p90r_300: [-7.38980930e-01 -1.54835424e-01 -1.56248425e-01 -7.12228548e-01
-5.59050822e-01 -6.75022883e-01 9.26856837e-01 -6.49178698e-01
-3.18350372e-01 -4.81758276e-01 3.24742321e-01 3.23670229e-02
-6.56928798e-01 -1.05371349e-01 8.62156231e-01 1.24415122e+00
-7.64331578e-01 -9.13689117e-01 -3.42466053e-01 -8.95327881e-01
9.72897706e-01 -7.92942046e-01 2.71782926e-01 1.45195324e-01
-5.91495776e-01 -5.38887941e-01 1.43836408e-01 -5.66776133e-01
-7.04538167e-01 1.21783891e-01 -7.26616601e-01 5.79723270e-02
-5.89374020e-01 -6.32632831e-01 -6.83713857e-01 -5.39856985e-01
2.61213583e-01 -4.67610229e-01 1.03171644e+00 2.86699610e+00
-6.73217138e-02 3.59030712e-01 -4.91359701e-01 4.53313247e+00
6.83692703e-02 -2.35219898e-01 -8.55419992e-02 6.05336970e-01
-1.21555515e-01 -6.15424408e-01 -4.86375884e-01 -8.48561693e-01
-7.50912569e-01 -7.57988845e-01 7.27987039e-02 -2.04031321e-01
-8.24163074e-01 -5.25936552e-01 2.58778069e-02 -6.63864225e-01
-4.40371072e-01 -8.76649215e-01 4.26311679e-01 3.90547186e-01
-5.16910919e-01 -7.04486335e-01 -8.63570498e-01 -5.91876633e-01
-6.64045640e-01 9.09774615e-01 1.87337480e-01 -7.31984656e-01
-8.31547755e-01 5.23475267e-01 -4.66845135e-01 2.97099934e+00
-7.41925247e-01 8.16746367e-01 -5.41925782e-01 -1.00886702e-01
-7.36933542e-01 -7.64105092e-01 -8.82714530e-01 1.41770992e-01
5.18910109e-02 5.44195403e-02 5.53290279e-01 -4.16515681e-01
-8.60839879e-02 -7.60820483e-01 8.37817445e-01 -3.25993427e-01
1.31812535e+00 -7.03487994e-01 2.19330589e-01 5.41254467e-02
9.50823780e-01 1.32510022e+00 1.09035488e+00 -5.60262127e-01
-5.68236460e-01 8.77627135e-01 -7.75119519e-01 1.27637594e-01
-4.10099707e-01 -7.15710346e-01 1.29892476e+00 -2.33342656e-01
-4.83198320e-01 -1.93161124e-01 -1.92176304e-01 1.04569997e+00
-5.11463989e-01 -8.82826421e-01 -6.49903227e-01 -6.49940412e-01
-3.82031228e-01 3.60781791e-03 -4.48948240e-01 7.89421573e-01
-3.65795229e-01 1.25447103e-01 1.99381962e+00 3.46204561e+00
-6.52047520e-01 -3.50226255e-03 2.90476465e-01 -6.72724220e-01
5.52298699e-01 1.08893512e+00 -8.67311459e-01 -8.79297297e-01
5.09422490e-02 5.42777276e-01 2.84470645e-01 3.36325780e-01
1.91429039e+00 -3.08001881e-01 -6.18342190e-02 -6.38062859e-01
1.29431453e-01 -6.09758879e-01 -4.06828619e-01 8.58257518e-01
-7.10025662e-01 -7.09905095e-01 -4.43728923e-01 1.32741015e+00
5.17627198e-01 -6.94097279e-01 4.88679818e-01 -4.81113748e-01
-7.92357239e-01 2.25622779e+00 -7.17380257e-01 -2.94684284e-01
-4.55497176e-01 1.16085685e-01 1.42502282e-01 -6.03958135e-01
1.02180064e+00 5.33560088e-01 1.42445942e-01 -7.35170107e-01
6.67051567e-01 1.23370582e+00 1.09001684e+00 8.03486400e+00
1.15889786e+00 7.87810255e-01 -5.42297625e-01 1.14428332e+00
1.81882663e-01 -4.89616548e-01 -2.22276396e-01 -2.19929281e-01
-4.08246128e-01 1.20200906e+00 -4.79899063e-01 1.02762453e-01
-5.08391217e-01 -1.12079163e-01 -7.26430680e-01 -1.11056033e-01
-6.87053680e-01 -5.41962966e-01 7.53442988e-01 -5.21445145e-01
-8.79789256e-01 1.39907272e-01 -7.78090879e-01 -4.54595740e-01
1.32737471e-01 -4.69408595e-01 1.13351116e+00 -6.68867198e-01
-6.87139316e-01 -4.44703601e-01 -6.68844662e-01 -8.38870799e-01
-6.96763278e-01 2.81668467e+00 -6.59145205e-01 -5.70669212e-01
3.68814842e+00 -8.42885685e-01 4.60735286e-01 -5.26715168e-01
-7.49959300e-01 -8.00874687e-01 3.65881629e-01 1.35484090e-02
-5.11922595e-01 -8.67966015e-01 1.30487424e+00 -5.41693662e-01
-3.59445736e-01 -6.35435172e-01 -3.81230076e-01 -3.93748776e-01
-4.91666190e-01 -5.47762583e-01 2.88897316e-02 -1.60947163e-01
-2.07489966e-02 -4.81725598e-01 -5.51858486e-01 9.56118084e-02
-3.48044818e-01 -8.23992703e-01 1.04588989e-01 -7.17748101e-02
1.36486938e-02 -8.70377696e-01 2.25606841e-01 -6.22277579e-01
-3.81235710e-01 1.59083243e+00 9.42855699e-02 1.92493861e+00
7.38231247e-01 -4.00294331e-01 9.81776856e-01 3.99640590e+00
6.72268631e-01 1.25711900e-01 -6.52640214e-01 -6.71223328e-01
-1.06922946e-01 -2.59439243e-01 -3.99361345e-01 -8.41371610e-01
1.41787894e-01 -8.89173098e-01 -1.47933800e-01 2.40029825e-01
1.30000648e+00 -8.45228744e-01 -5.96459310e-01 -5.43861617e-01
-7.40541542e-01 -5.23574788e-01 -6.28150438e-01 -5.22802933e-01
-7.89704762e-01 -4.73256602e-01 -8.23711963e-02 -7.34647274e-01
-1.80469406e-02 1.12072203e+00 -1.80764118e-01 2.09074658e+00
-5.09842530e-01 -1.65667310e-01 -1.53132835e-01 -5.74149884e-01]
Unique values in p00r_300: [-6.75829057e-01 -1.93095414e-01 -1.11893739e-01 -6.38663700e-01
-5.17095478e-01 -6.09831392e-01 7.82043991e-01 -6.09721524e-01
-3.23619268e-01 -4.59186710e-01 1.49712698e-01 -1.93888302e-02
-6.18528788e-01 -1.32762043e-01 7.31814699e-01 1.05507949e+00
-6.94063351e-01 -8.25629644e-01 -3.31641494e-01 -8.11637081e-01
7.78156362e-01 -7.10155694e-01 2.03857790e-01 8.28154313e-02
-5.47147601e-01 -4.97141801e-01 7.85343443e-02 -4.95548248e-01
-6.35541390e-01 6.13714956e-02 -6.37531217e-01 1.20380482e-02
-4.98525008e-01 -5.84650074e-01 -6.23662524e-01 -4.92244703e-01
1.72362362e-01 -3.85474825e-01 8.73957305e-01 2.73219697e+00
-1.62264827e-01 4.26269604e-01 -4.58350025e-01 4.94443624e+00
-4.95883823e-02 -1.66418204e-01 -1.10503959e-01 4.93871151e-01
-1.43630501e-01 -5.68548341e-01 -4.49760619e-01 -7.60810371e-01
-6.58875615e-01 -6.88531462e-01 2.50944715e-02 -2.11744765e-01
-7.29905600e-01 -4.34441107e-01 -2.47122525e-02 -6.04231891e-01
-4.14314646e-01 -7.91056688e-01 3.46873704e-01 3.08373031e-01
-4.79321623e-01 -6.35493499e-01 -7.83287721e-01 -5.47495985e-01
-6.11564861e-01 7.28152440e-01 1.15681859e-01 -6.61707762e-01
-7.49529674e-01 4.26560706e-01 -4.35948268e-01 2.91702837e+00
-6.51720124e-01 6.96788477e-01 -5.01883018e-01 -1.25880752e-01
-6.74293725e-01 -6.94276514e-01 -7.90900995e-01 7.19563635e-02
8.59706516e-04 3.42234886e-03 5.97409789e-01 -4.09935899e-01
-1.54070757e-01 -6.91186130e-01 7.08179042e-01 -3.18965382e-01
1.10134603e+00 -6.37421349e-01 1.49562451e-01 -2.03907868e-02
7.68399728e-01 1.65561487e+00 9.28421671e-01 -4.72748338e-01
-5.28502946e-01 7.93641145e-01 -7.03758948e-01 7.12549000e-02
-3.89800986e-01 -6.17650784e-01 1.09477275e+00 -2.36274388e-01
-4.66946944e-01 -2.07846806e-01 -2.07007304e-01 9.44235118e-01
-4.74063934e-01 -7.95877348e-01 -5.95183294e-01 -5.95238698e-01
-4.05893328e-01 -6.07413699e-02 -4.26919391e-01 6.45516849e-01
-3.58529049e-01 6.77363142e-02 2.15447090e+00 3.74369416e+00
-6.19190811e-01 1.47355705e-01 2.06834550e-01 -6.16442239e-01
3.53287353e-01 9.28093007e-01 -7.88601002e-01 -7.99960766e-01
-3.82006346e-02 3.56639728e-01 1.52576772e-01 2.27822112e-01
1.79598268e+00 -2.37934613e-01 -1.69516100e-01 -5.85930925e-01
1.79226750e-01 -5.63870040e-01 -4.01890197e-01 7.29213556e-01
-6.67679122e-01 -6.67661280e-01 -4.19996782e-01 1.65769954e+00
4.21677694e-01 -6.47523550e-01 3.93994771e-01 -4.04859444e-01
-7.04110149e-01 2.24218670e+00 -6.55593667e-01 -2.87401404e-01
-3.78247028e-01 4.98588554e-02 7.23366750e-02 -5.58882794e-01
8.11792804e-01 4.35735135e-01 7.24456038e-02 -6.64310783e-01
5.54007324e-01 1.04836535e+00 9.28985095e-01 8.85969173e+00
9.87355872e-01 6.44033165e-01 -5.02182572e-01 1.14437288e+00
1.09795952e-01 -4.40628447e-01 -2.76833439e-01 -2.75114994e-01
-4.43398618e-01 1.01994059e+00 -3.92807794e-01 3.69911793e-02
-4.88865095e-01 -1.38453569e-01 -6.66319391e-01 -1.44172328e-01
-6.29827326e-01 -5.04389317e-01 5.42485293e-01 -4.82726585e-01
-7.82280412e-01 7.66064935e-02 -7.04856686e-01 -4.26367235e-01
6.98425827e-02 -4.40891379e-01 9.64753160e-01 -6.08365549e-01
-6.30487472e-01 -4.15737293e-01 -6.13061692e-01 -7.62402515e-01
-6.32682010e-01 2.67088700e+00 -6.08487624e-01 -5.26900943e-01
3.68934248e+00 -7.56674554e-01 3.05847012e-01 -4.92507634e-01
-6.79401168e-01 -7.23793383e-01 2.15351650e-01 -2.99239290e-02
-4.74442367e-01 -7.76135987e-01 1.27532212e+00 -5.16007130e-01
-3.51080578e-01 -5.85798520e-01 -3.60930176e-01 -3.92346725e-01
-4.15772037e-01 -4.65652945e-01 -2.01391238e-02 -1.94747187e-01
-9.39261327e-02 -4.59158539e-01 -5.14914087e-01 4.54294000e-02
-3.93623821e-01 -7.30672796e-01 -2.96713270e-02 -1.00702251e-01
-2.98441105e-02 -7.79733452e-01 1.44914199e-01 -5.49376884e-01
-3.69374970e-01 1.88932334e+00 2.93642900e-02 2.24663775e+00
5.80056315e-01 -3.82151559e-01 8.16084220e-01 3.61775940e+00
5.57406651e-01 6.79203662e-02 -6.07653756e-01 -6.16178368e-01
-1.27221702e-01 -2.58097697e-01 -3.89633837e-01 -7.53286870e-01
7.19760834e-02 -8.02161127e-01 -1.62232899e-01 1.70503061e-01
1.09564606e+00 -7.59508391e-01 -5.48004945e-01 -5.07043047e-01
-6.92412518e-01 -4.32307607e-01 -5.31069345e-01 -5.00271624e-01
-7.15181440e-01 -3.99661853e-01 -1.13450669e-01 -6.64323929e-01
-9.18470964e-02 9.20252016e-01 -1.89484803e-01 2.33581846e+00
-4.77950624e-01 -2.01113884e-01 -2.29644760e-01 -5.30945391e-01]
Unique values in p10r_300: [-6.36833335e-01 -1.56917334e-01 -6.84671853e-02 -5.93155396e-01
-4.73249968e-01 -5.67343067e-01 6.73190659e-01 -5.92606603e-01
-3.24661412e-01 -4.18584567e-01 4.71150478e-02 -2.06658388e-02
-6.01324285e-01 -1.31786436e-01 6.39102501e-01 9.04686722e-01
-6.47267031e-01 -7.75412226e-01 -3.11288939e-01 -7.62299808e-01
6.41838175e-01 -6.57627775e-01 1.72728086e-01 6.82336233e-02
-5.04137388e-01 -4.68170733e-01 2.95918114e-02 -4.53671660e-01
-5.90203355e-01 1.47055990e-02 -5.91871287e-01 7.00094579e-03
-4.42782019e-01 -5.40593147e-01 -5.78888441e-01 -4.50503252e-01
1.51389828e-01 -3.46589084e-01 7.63807793e-01 2.57956592e+00
-2.22770814e-01 4.32907278e-01 -4.31088256e-01 5.61086697e+00
-1.35819483e-01 -1.49716708e-01 -1.05955040e-01 4.30155024e-01
-1.36931991e-01 -5.25149023e-01 -4.01083713e-01 -7.11972522e-01
-6.12958361e-01 -6.41693716e-01 1.89392620e-02 -2.01144895e-01
-6.81986052e-01 -3.94198933e-01 -2.57699436e-02 -5.60168139e-01
-3.74774818e-01 -7.41389475e-01 2.86183954e-01 2.63627078e-01
-4.38077489e-01 -5.90156931e-01 -7.35893506e-01 -5.04447431e-01
-5.66886292e-01 6.06854705e-01 9.98348048e-02 -6.15765328e-01
-7.01248348e-01 3.45175037e-01 -3.95871010e-01 2.84182588e+00
-6.05895347e-01 6.03787434e-01 -4.60931974e-01 -1.22868138e-01
-6.35472959e-01 -6.47291071e-01 -7.41217542e-01 1.86217580e-02
-4.39530579e-02 -4.16824483e-02 5.70387340e-01 -3.89324459e-01
-1.75180860e-01 -6.44283488e-01 6.20872963e-01 -2.95640054e-01
9.31048673e-01 -5.91880406e-01 1.30159338e-01 -6.43785959e-02
6.37975071e-01 1.56918197e+00 7.94049427e-01 -4.31438090e-01
-4.86125046e-01 7.51853725e-01 -6.56501174e-01 1.81434295e-02
-3.71201032e-01 -5.72708304e-01 9.32714947e-01 -2.23993577e-01
-4.58018895e-01 -2.00663250e-01 -1.99903894e-01 8.92823844e-01
-4.32900433e-01 -7.46182293e-01 -5.56157475e-01 -5.56246177e-01
-4.25341682e-01 -9.86408422e-02 -3.87430212e-01 5.40294924e-01
-3.10483988e-01 1.51424779e-02 2.28579596e+00 3.91919239e+00
-6.01935252e-01 2.90444974e-01 1.38192272e-01 -5.71734238e-01
1.95003106e-01 7.94687751e-01 -7.38245439e-01 -7.53338071e-01
-5.86361672e-02 2.24631286e-01 9.99011242e-02 1.57797937e-01
1.89947732e+00 -2.17129522e-01 -2.29741809e-01 -5.41778606e-01
2.10438940e-01 -5.20408017e-01 -3.81786433e-01 6.36184448e-01
-6.38625616e-01 -6.38660434e-01 -3.80641595e-01 1.57114669e+00
3.40864278e-01 -6.17104151e-01 3.48631935e-01 -3.74547674e-01
-6.58318325e-01 2.37625559e+00 -6.09527162e-01 -2.71642389e-01
-3.39607312e-01 3.51518619e-02 1.89599868e-02 -5.15628877e-01
6.64635459e-01 3.71578438e-01 1.90561499e-02 -6.18290438e-01
4.88516073e-01 9.04239066e-01 7.95458714e-01 9.19184787e+00
8.43764087e-01 5.38993406e-01 -4.61223779e-01 1.08442051e+00
9.63779075e-02 -4.00356687e-01 -3.16459364e-01 -3.15063341e-01
-4.53731348e-01 8.70581984e-01 -3.53715101e-01 -1.23145717e-02
-4.77397416e-01 -1.36931162e-01 -6.29582141e-01 -1.72270269e-01
-5.94160134e-01 -4.62429134e-01 4.20149089e-01 -4.41424130e-01
-7.32757345e-01 6.54979492e-02 -6.57573061e-01 -3.86648473e-01
5.89489111e-02 -4.00698232e-01 8.26728298e-01 -5.64129893e-01
-5.85115001e-01 -3.76048979e-01 -5.68442310e-01 -7.13464791e-01
-5.87488405e-01 2.52204215e+00 -5.63873734e-01 -4.85238024e-01
3.86382401e+00 -7.08130226e-01 2.21016880e-01 -4.69117442e-01
-6.32709928e-01 -6.76132538e-01 9.34930147e-02 -3.05938491e-02
-4.33266847e-01 -7.26653062e-01 1.20600880e+00 -4.70164460e-01
-3.13465044e-01 -5.41728867e-01 -3.37630166e-01 -3.91954022e-01
-3.76043176e-01 -4.24672685e-01 -6.27628902e-02 -2.17238120e-01
-1.08076431e-01 -4.18556381e-01 -4.72827182e-01 3.29823894e-02
-4.12812294e-01 -6.82678260e-01 -1.31973788e-01 -9.73874061e-02
-3.05192398e-02 -7.30282058e-01 8.75242711e-02 -5.06098783e-01
-3.31725254e-01 1.78969389e+00 -1.90567650e-02 2.38113006e+00
4.79936004e-01 -3.43806157e-01 6.90682393e-01 3.41504910e+00
4.81593988e-01 1.53057893e-02 -5.82623879e-01 -5.80949315e-01
-1.17696056e-01 -2.44404193e-01 -3.41583629e-01 -7.04612481e-01
1.86391669e-02 -7.53138284e-01 -1.63750716e-01 1.13728714e-01
9.33461040e-01 -7.10850398e-01 -5.02447073e-01 -4.65452468e-01
-6.61077211e-01 -3.92122308e-01 -4.88256385e-01 -5.02754629e-01
-6.67470399e-01 -3.60421647e-01 -1.13482289e-01 -6.18088993e-01
-1.06223634e-01 7.72437601e-01 -1.71756294e-01 2.21078046e+00
-4.37206218e-01 -1.99622036e-01 -2.87220810e-01 -4.88369957e-01]
Unique values in Country_encoded: [ 0.60568138 0.51463124 -1.67057217 1.06093209 -1.9437226 -1.03322118
0.15043067 -1.57952203 -1.12427132 0.96988195 0.69673152 -0.48692033
0.24148081 -0.12271976 -1.48847189 -0.76007075 -0.66902061 -1.39742175
0.05938053 -0.03166961 0.87883181 0.78778166 -1.76162231 -1.3063716
-0.57797047 -0.30482004 -0.85112089 0.4235811 -0.39587018 0.33253095
-0.2137699 -1.21532146 -1.85267246 -0.94217104]
# Plot histograms for Latitude and Longitude
plt.figure(figsize=(10, 4))
plt.subplot(1, 2, 1)
plt.hist(df['Latitude'], bins=20)
plt.xlabel('Latitude')
plt.ylabel('Frequency')
plt.subplot(1, 2, 2)
plt.hist(df['Longitude'], bins=20)
plt.xlabel('Longitude')
plt.ylabel('Frequency')
plt.tight_layout()
plt.show()
# Calculate mean, median, and standard deviation for p90_1200, p00_1200, and p10_1200
statistics_1200 = df[['p90_1200', 'p00_1200', 'p10_1200']].describe()
statistics_300 = df[['p90_300', 'p00_300', 'p10_300']].describe()
# Create a DataFrame to compare statistics across time intervals
comparison_stats = pd.concat([statistics_1200, statistics_300], keys=['1200', '300'])
comparison_stats = comparison_stats.rename(index={'1200': 'Statistics for 1200', '300': 'Statistics for 300'})
print(comparison_stats)
p90_1200 p00_1200 p10_1200 \
Statistics for 1200 count 2.760000e+02 2.760000e+02 2.760000e+02
mean -5.792468e-17 -1.287215e-17 1.930823e-17
std 1.001817e+00 1.001817e+00 1.001817e+00
min -1.606461e+00 -1.536982e+00 -1.498838e+00
25% -7.151712e-01 -7.026149e-01 -6.833262e-01
50% -3.670322e-01 -3.666486e-01 -3.975284e-01
75% 7.049230e-01 5.991319e-01 5.246408e-01
max 3.440412e+00 3.963610e+00 4.471422e+00
Statistics for 300 count NaN NaN NaN
mean NaN NaN NaN
std NaN NaN NaN
min NaN NaN NaN
25% NaN NaN NaN
50% NaN NaN NaN
75% NaN NaN NaN
max NaN NaN NaN
p90_300 p00_300 p10_300
Statistics for 1200 count NaN NaN NaN
mean NaN NaN NaN
std NaN NaN NaN
min NaN NaN NaN
25% NaN NaN NaN
50% NaN NaN NaN
75% NaN NaN NaN
max NaN NaN NaN
Statistics for 300 count 2.760000e+02 2.760000e+02 2.760000e+02
mean 8.366898e-17 -1.287215e-17 -1.351576e-16
std 1.001817e+00 1.001817e+00 1.001817e+00
min -1.401155e+00 -1.351009e+00 -1.335402e+00
25% -7.848346e-01 -7.573392e-01 -7.504482e-01
50% -2.745483e-01 -2.833819e-01 -2.697757e-01
75% 6.557133e-01 5.757628e-01 5.839749e-01
max 3.903643e+00 4.980302e+00 5.563019e+00
# Scatter plot of Latitude and Longitude on a map
plt.figure(figsize=(10, 8))
plt.scatter(df['Longitude'], df['Latitude'])
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.title('Geographic Distribution')
plt.show()
# Select variables for correlation analysis
variables = ['p90_1200', 'p00_1200', 'p10_1200', 'Latitude', 'Longitude']
# Compute correlation matrix
corr_matrix = df[variables].corr()
# Plot correlation matrix as a heatmap
plt.figure(figsize=(8, 6))
sns.heatmap(corr_matrix, annot=True, cmap='coolwarm')
plt.title('Correlation Matrix for Multiple Variables')
plt.show()
# Create a scatter plot of p90_1200 vs. Longitude with color encoding for Latitude
plt.scatter(df['Longitude'], df['p90_1200'], c=df['Latitude'], cmap='viridis')
plt.colorbar(label='Latitude')
plt.xlabel('Longitude')
plt.ylabel('p90_1200')
plt.title('Scatter Plot of p90_1200 vs. Longitude with Color Encoding for Latitude')
plt.show()
df = df.drop("Country", axis=1)
df
| Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | p90u_1200 | p00u_1200 | p10u_1200 | p90r_1200 | p00r_1200 | ... | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | Country_encoded | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1.352765 | 0.251194 | -0.464402 | -0.508016 | -0.554848 | -0.593107 | -0.660152 | -0.734917 | -0.252291 | -0.282518 | ... | -1.172443 | -1.136296 | -1.125151 | -1.191514 | -1.198046 | -1.215751 | -0.738981 | -0.675829 | -0.636833 | 0.605681 |
| 1 | -0.126329 | -0.064588 | -0.774040 | -0.731805 | -0.679515 | -0.964721 | -0.953322 | -0.919337 | -0.444835 | -0.404765 | ... | -0.586885 | -0.600261 | -0.556108 | -0.716401 | -0.736024 | -0.708998 | -0.154835 | -0.193095 | -0.156917 | 0.514631 |
| 2 | -4.916056 | -0.579314 | -1.002907 | -0.916580 | -0.857975 | -1.183329 | -1.120005 | -1.079853 | -0.644420 | -0.576372 | ... | 0.414370 | 0.496365 | 0.605076 | 0.653952 | 0.779507 | 0.935261 | -0.156248 | -0.111894 | -0.068467 | -1.670572 |
| 3 | -0.469286 | -1.226995 | -0.889115 | -0.813688 | -0.764634 | -0.908713 | -0.841270 | -0.801030 | -0.714629 | -0.655143 | ... | -1.145335 | -1.094991 | -1.071174 | -1.169357 | -1.162423 | -1.166418 | -0.712229 | -0.638664 | -0.593155 | 1.060932 |
| 4 | -0.020197 | 0.018589 | 0.051419 | 0.029799 | 0.051246 | 0.176309 | 0.148003 | 0.179467 | -0.085040 | -0.085873 | ... | -0.741186 | -0.728155 | -0.685837 | -0.701982 | -0.714859 | -0.682794 | -0.559051 | -0.517095 | -0.473250 | 0.514631 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | -1.506439 | 1.501828 | 1.792834 | 1.899641 | 1.913771 | 0.839405 | 1.051898 | 1.110167 | 2.454943 | 2.384831 | ... | 1.727114 | 2.251499 | 2.276462 | 1.196198 | 1.746700 | 1.828051 | 2.090747 | 2.335818 | 2.210780 | -1.397422 |
| 272 | 0.096301 | -0.957393 | -0.854920 | -0.820254 | -0.771264 | -0.789761 | -0.786267 | -0.743154 | -0.772925 | -0.718363 | ... | 0.245594 | 0.188036 | 0.253678 | 0.620326 | 0.569365 | 0.671899 | -0.509843 | -0.477951 | -0.437206 | 1.060932 |
| 273 | -0.461599 | 1.689799 | 2.357024 | 2.340021 | 2.270520 | 2.538004 | 2.634711 | 2.644594 | 1.762702 | 1.682191 | ... | 0.566912 | 0.570582 | 0.541617 | 0.867854 | 0.941671 | 0.931923 | -0.165667 | -0.201114 | -0.199622 | -0.395870 |
| 274 | 0.461080 | 0.470339 | 0.061055 | -0.037393 | -0.131383 | -0.141744 | -0.234249 | -0.340844 | 0.257537 | 0.153308 | ... | -0.455104 | -0.551699 | -0.640980 | -0.537094 | -0.643647 | -0.744355 | -0.153133 | -0.229645 | -0.287221 | 0.878832 |
| 275 | 0.074844 | -1.154910 | -0.616189 | -0.577300 | -0.524737 | -0.479518 | -0.452401 | -0.391292 | -0.648693 | -0.600271 | ... | -0.497452 | -0.464913 | -0.420298 | -0.360175 | -0.330085 | -0.282576 | -0.574150 | -0.530945 | -0.488370 | 1.060932 |
276 rows × 57 columns
# Get all the features (column names)
features = df.columns.tolist()
# Print the list of features
print("All Features:", features)
All Features: ['Latitude', 'Longitude', 'p90_1200', 'p00_1200', 'p10_1200', 'p90u_1200', 'p00u_1200', 'p10u_1200', 'p90r_1200', 'p00r_1200', 'p10r_1200', 'p90_30', 'p00_30', 'p10_30', 'p90u_30', 'p00u_30', 'p10u_30', 'p90r_30', 'p00r_30', 'p10r_30', 'p90_75', 'p00_75', 'p10_75', 'p90u_75', 'p00u_75', 'p10u_75', 'p90r_75', 'p00r_75', 'p10r_75', 'p90_150', 'p00_150', 'p10_150', 'p90u_150', 'p00u_150', 'p10u_150', 'p90r_150', 'p00r_150', 'p10r_150', 'p90_600', 'p00_600', 'p10_600', 'p90u_600', 'p00u_600', 'p10u_600', 'p90r_600', 'p00r_600', 'p10r_600', 'p90_300', 'p00_300', 'p10_300', 'p90u_300', 'p00u_300', 'p10u_300', 'p90r_300', 'p00r_300', 'p10r_300', 'Country_encoded']
from scipy.stats import chi2_contingency
from itertools import combinations
# Perform chi-square tests for all possible combinations of features
def perform_chi_square_tests(data, features):
results = []
for feature1, feature2 in combinations(features, 2):
contingency_table = pd.crosstab(data[feature1], data[feature2])
chi2, p_value, _, _ = chi2_contingency(contingency_table)
results.append((feature1, feature2, chi2, p_value))
return results
# Specify the list of features for the chi-square tests
features =['Latitude', 'Longitude', 'p90_1200', 'p00_1200', 'p10_1200', 'p90u_1200', 'p00u_1200', 'p10u_1200', 'p90r_1200', 'p00r_1200', 'p10r_1200', 'p90_30', 'p00_30', 'p10_30', 'p90u_30', 'p00u_30', 'p10u_30', 'p90r_30', 'p00r_30', 'p10r_30', 'p90_75', 'p00_75', 'p10_75', 'p90u_75', 'p00u_75', 'p10u_75', 'p90r_75', 'p00r_75', 'p10r_75', 'p90_150', 'p00_150', 'p10_150', 'p90u_150', 'p00u_150', 'p10u_150', 'p90r_150', 'p00r_150', 'p10r_150', 'p90_600', 'p00_600', 'p10_600', 'p90u_600', 'p00u_600', 'p10u_600', 'p90r_600', 'p00r_600', 'p10r_600', 'p90_300', 'p00_300', 'p10_300', 'p90u_300', 'p00u_300', 'p10u_300', 'p90r_300', 'p00r_300', 'p10r_300', 'Country_encoded']
# Perform the chi-square tests
chi_square_results = perform_chi_square_tests(df, features)
# Print the results
for result in chi_square_results:
feature1, feature2, chi2_statistic, p_value = result
print("Chi-square test between", feature1, "and", feature2)
print("Chi-square statistic:", chi2_statistic)
print("P-value:", p_value)
print()
Chi-square test between Latitude and Longitude Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between Latitude and p90_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90r_1200 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between Latitude and p00r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between Latitude and p00u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between Latitude and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between Latitude and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00_75 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between Latitude and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between Latitude and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between Latitude and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between Latitude and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between Latitude and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between Latitude and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between Latitude and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between Longitude and p90_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90u_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00u_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10u_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90r_1200 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between Longitude and p00r_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10r_1200 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90_30 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00_30 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10_30 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90u_30 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between Longitude and p00u_30 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between Longitude and p10u_30 Chi-square statistic: 75072.0 P-value: 0.2422935108134661 Chi-square test between Longitude and p90r_30 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00r_30 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10r_30 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00_75 Chi-square statistic: 75072.0 P-value: 0.2422935108134661 Chi-square test between Longitude and p10_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90u_75 Chi-square statistic: 74796.00000000001 P-value: 0.24432170848750906 Chi-square test between Longitude and p00u_75 Chi-square statistic: 74796.00000000001 P-value: 0.24432170848750906 Chi-square test between Longitude and p10u_75 Chi-square statistic: 74796.00000000001 P-value: 0.24432170848750906 Chi-square test between Longitude and p90r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00_150 Chi-square statistic: 75347.99999999999 P-value: 0.24028111743839922 Chi-square test between Longitude and p10_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00u_150 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between Longitude and p10u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00u_600 Chi-square statistic: 75072.0 P-value: 0.2422935108134661 Chi-square test between Longitude and p10u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p90r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p00r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and p10r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between Longitude and Country_encoded Chi-square statistic: 9108.0 P-value: 0.22970721827216425 Chi-square test between p90_1200 and p00_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90r_1200 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_1200 and p00r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_1200 and p00u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00u_600 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_1200 and Country_encoded Chi-square statistic: 9108.000000000002 P-value: 0.40144847024690966 Chi-square test between p00_1200 and p10_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90r_1200 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00_1200 and p00r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_1200 and p00u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_1200 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10_1200 and p90u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90r_1200 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_1200 and p00r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_1200 and p00u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00u_600 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_1200 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90u_1200 and p00u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90r_1200 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_1200 and p00r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_1200 and p00u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90u_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00_75 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90u_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90u_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90u_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90u_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90u_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_1200 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00u_1200 and p10u_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90r_1200 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_1200 and p00r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00u_1200 and p00u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00u_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00u_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00u_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00u_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00u_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00u_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_1200 and Country_encoded Chi-square statistic: 9108.000000000002 P-value: 0.40144847024690966 Chi-square test between p10u_1200 and p90r_1200 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10u_1200 and p00r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10u_1200 and p00u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10u_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00_75 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10u_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10u_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10u_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10u_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10u_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00u_600 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10u_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_1200 and p10r_300 Chi-square statistic: 75899.99999999999 P-value: 0.23948344171998676 Chi-square test between p10u_1200 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90r_1200 and p00r_1200 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10r_1200 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90u_30 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p90r_1200 and p00u_30 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p90r_1200 and p10u_30 Chi-square statistic: 75348.00000000001 P-value: 0.2410841445243976 Chi-square test between p90r_1200 and p90r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00_75 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p90r_1200 and p10_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p90r_1200 and p00u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p90r_1200 and p10u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p90r_1200 and p90r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00u_150 Chi-square statistic: 75348.00000000001 P-value: 0.2410841445243976 Chi-square test between p90r_1200 and p10u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00u_600 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p90r_1200 and p10u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p90r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p00r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and p10r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_1200 and Country_encoded Chi-square statistic: 9108.000000000002 P-value: 0.31045659585425467 Chi-square test between p00r_1200 and p10r_1200 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00r_1200 and p00u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00r_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00r_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00r_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00r_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00r_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00r_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00r_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00r_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_1200 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10r_1200 and p90_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10r_1200 and p00u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10r_1200 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10r_1200 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10r_1200 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10r_1200 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10r_1200 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10r_1200 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10r_1200 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10r_1200 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_1200 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90_30 and p00_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_30 and p00u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_30 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_30 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_30 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_30 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_30 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_30 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_30 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00u_600 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_30 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00_30 and p10_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_30 and p00u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00_30 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00_30 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_30 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00_30 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00_30 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00_30 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00_30 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_30 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10_30 and p90u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_30 and p00u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_30 and p10u_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_30 and p90r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00_75 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_30 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_30 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_30 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_30 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_30 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_30 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90u_30 and p00u_30 Chi-square statistic: 75624.0 P-value: 0.0789004181855964 Chi-square test between p90u_30 and p10u_30 Chi-square statistic: 75624.0 P-value: 0.0789004181855964 Chi-square test between p90u_30 and p90r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00_75 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p90u_30 and p10_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p90u_30 and p00u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p90u_30 and p10u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p90u_30 and p90r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00u_150 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p90u_30 and p10u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00u_600 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p90u_30 and p10u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p90r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p00r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and p10r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.31045659585425944 Chi-square test between p00u_30 and p10u_30 Chi-square statistic: 75624.00000000001 P-value: 0.07890041818559086 Chi-square test between p00u_30 and p90r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00_75 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p00u_30 and p10_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p00u_30 and p00u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p00u_30 and p10u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p00u_30 and p90r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00u_150 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p00u_30 and p10u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00u_600 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p00u_30 and p10u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p90r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p00r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and p10r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.31045659585425944 Chi-square test between p10u_30 and p90r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10r_30 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00_75 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p10u_30 and p10_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p10u_30 and p00u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p10u_30 and p10u_75 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p10u_30 and p90r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00u_150 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p10u_30 and p10u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00u_600 Chi-square statistic: 75348.00000000001 P-value: 0.2410841445243976 Chi-square test between p10u_30 and p10u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p90r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p00r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and p10r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.31045659585425944 Chi-square test between p90r_30 and p00r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00_75 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90r_30 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90r_30 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90r_30 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90r_30 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90r_30 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90r_30 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_30 and Country_encoded Chi-square statistic: 9107.999999999998 P-value: 0.40144847024692004 Chi-square test between p00r_30 and p10r_30 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00r_30 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00r_30 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00r_30 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p00r_30 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00r_30 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00r_30 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10r_30 and p90_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00_75 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10r_30 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10r_30 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10r_30 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10r_30 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10r_30 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10r_30 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_30 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90_75 and p00_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_75 and p10_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_75 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_75 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p90_75 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_75 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_75 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_75 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00_75 and p10_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.0792797328485861 Chi-square test between p00_75 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.0792797328485861 Chi-square test between p00_75 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.0792797328485861 Chi-square test between p00_75 and p90r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10r_75 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00u_150 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p00_75 and p10u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00u_600 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p00_75 and p10u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p90r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p00r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and p10r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_75 and Country_encoded Chi-square statistic: 9108.000000000002 P-value: 0.31045659585425467 Chi-square test between p10_75 and p90u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_75 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_75 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.24028111743837594 Chi-square test between p10_75 and p90r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10_75 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_75 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_75 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90u_75 and p00u_75 Chi-square statistic: 75348.00000000001 P-value: 0.017201147564985513 Chi-square test between p90u_75 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.017201147564985513 Chi-square test between p90u_75 and p90r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00u_150 Chi-square statistic: 75072.0 P-value: 0.2422935108134661 Chi-square test between p90u_75 and p10u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00u_600 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p90u_75 and p10u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p90r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p00r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and p10r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p90u_75 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.22970721827216425 Chi-square test between p00u_75 and p10u_75 Chi-square statistic: 75348.00000000001 P-value: 0.017201147564985513 Chi-square test between p00u_75 and p90r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00u_150 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p00u_75 and p10u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00u_600 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p00u_75 and p10u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p90r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p00r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and p10r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p00u_75 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.22970721827216425 Chi-square test between p10u_75 and p90r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10r_75 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00u_150 Chi-square statistic: 75072.00000000001 P-value: 0.2422935108134544 Chi-square test between p10u_75 and p10u_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10r_150 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00u_600 Chi-square statistic: 75072.0 P-value: 0.2422935108134661 Chi-square test between p10u_75 and p10u_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10r_600 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10u_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p90r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p00r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and p10r_300 Chi-square statistic: 75348.0 P-value: 0.24028111743838765 Chi-square test between p10u_75 and Country_encoded Chi-square statistic: 9108.000000000002 P-value: 0.22970721827216012 Chi-square test between p90r_75 and p00r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90r_75 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00u_600 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90r_75 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_75 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00r_75 and p10r_75 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00r_75 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00r_75 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_75 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10r_75 and p90_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p10r_75 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10r_75 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_75 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90_150 and p00_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90_150 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00_150 and p10_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_150 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00u_600 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p00_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10_150 and p90u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_150 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90u_150 and p00u_150 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90u_150 and p10u_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00u_150 and p10u_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p90r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p00r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p10r_150 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p90_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p00_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p10_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p90u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p00u_600 Chi-square statistic: 75348.0 P-value: 0.24108414452440924 Chi-square test between p00u_150 and p10u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p90r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p00r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p10r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p90_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p00_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p10_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p90u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p00u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p10u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p90r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p00r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and p10r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_150 and Country_encoded Chi-square statistic: 9078.776470588236 P-value: 0.3904815408394916 Chi-square test between p10u_150 and p90r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10u_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90r_150 and p00r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p00u_600 Chi-square statistic: 75624.00000000001 P-value: 0.23988173660144724 Chi-square test between p90r_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00r_150 and p10r_150 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00r_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10r_150 and p90_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10r_150 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_150 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90_600 and p00_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90_600 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00_600 and p10_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00_600 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10_600 and p90u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p10_600 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90u_600 and p00u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p90u_600 and p10u_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00u_600 and p10u_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p90r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p00r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p10r_600 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p90_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p00_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p10_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p90u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p00u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p10u_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p90r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p00r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and p10r_300 Chi-square statistic: 75624.0 P-value: 0.23988173660145884 Chi-square test between p00u_600 and Country_encoded Chi-square statistic: 9096.519327731094 P-value: 0.34106391374156725 Chi-square test between p10u_600 and p90r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90r_600 and p00r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00r_600 and p10r_600 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_600 and p00r_300 Chi-square statistic: 75899.99999999999 P-value: 0.23948344171998676 Chi-square test between p00r_600 and p10r_300 Chi-square statistic: 75899.99999999999 P-value: 0.23948344171998676 Chi-square test between p00r_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10r_600 and p90_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10r_600 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90_300 and p00_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90_300 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00_300 and p10_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_300 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_300 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_300 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_300 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_300 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00_300 and Country_encoded Chi-square statistic: 9108.000000000002 P-value: 0.40144847024690966 Chi-square test between p10_300 and p90u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_300 and p00u_300 Chi-square statistic: 75899.99999999999 P-value: 0.23948344171998676 Chi-square test between p10_300 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_300 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_300 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10_300 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90u_300 and p00u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_300 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_300 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_300 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90u_300 and Country_encoded Chi-square statistic: 9108.000000000002 P-value: 0.40144847024690966 Chi-square test between p00u_300 and p10u_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_300 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_300 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00u_300 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10u_300 and p90r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_300 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p10u_300 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p90r_300 and p00r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p90r_300 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p00r_300 and p10r_300 Chi-square statistic: 75900.0 P-value: 0.2394834417199751 Chi-square test between p00r_300 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149 Chi-square test between p10r_300 and Country_encoded Chi-square statistic: 9108.0 P-value: 0.4014484702469149
# Specify the list of features for the chi-square tests
features = ['Latitude', 'Longitude', 'p90_1200', 'p00_1200', 'p10_1200', 'p90u_1200', 'p00u_1200', 'p10u_1200', 'p90r_1200', 'p00r_1200', 'p10r_1200', 'p90_30', 'p00_30', 'p10_30', 'p90u_30', 'p00u_30', 'p10u_30', 'p90r_30', 'p00r_30', 'p10r_30', 'p90_75', 'p00_75', 'p10_75', 'p90u_75', 'p00u_75', 'p10u_75', 'p90r_75', 'p00r_75', 'p10r_75', 'p90_150', 'p00_150', 'p10_150', 'p90u_150', 'p00u_150', 'p10u_150', 'p90r_150', 'p00r_150', 'p10r_150', 'p90_600', 'p00_600', 'p10_600', 'p90u_600', 'p00u_600', 'p10u_600', 'p90r_600', 'p00r_600', 'p10r_600', 'p90_300', 'p00_300', 'p10_300', 'p90u_300', 'p00u_300', 'p10u_300', 'p90r_300', 'p00r_300', 'p10r_300', 'Country_encoded']
# Perform the chi-square test for independence
def perform_chi_square_tests(data):
results = []
columns = data.columns
for col1, col2 in combinations(columns, 2):
contingency_table = pd.crosstab(data[col1], data[col2])
chi2, p_value, _, _ = chi2_contingency(contingency_table)
results.append((col1, col2, chi2, p_value))
return results
# Perform the chi-square tests for independence
chi_square_results = perform_chi_square_tests(df)
# Sort the results based on p-values in ascending order
chi_square_results.sort(key=lambda x: x[3])
# Identify the independent and dependent variables based on p-values
independent_variables = []
dependent_variables = []
for result in chi_square_results:
feature1, feature2, _, p_value = result
if p_value < 0.05: # Set the desired significance level
dependent_variables.append((feature1, feature2))
else:
independent_variables.append((feature1, feature2))
# Print the independent and dependent variables
print("Independent variables:")
for pair in independent_variables:
print(pair[0], "and", pair[1])
print("\nDependent variables:")
for pair in dependent_variables:
print(pair[0], "and", pair[1])
Independent variables: p00u_30 and p10u_30 p90u_30 and p00u_30 p90u_30 and p10u_30 p00_75 and p90u_75 p00_75 and p00u_75 p00_75 and p10u_75 p10u_75 and Country_encoded Longitude and Country_encoded p90u_75 and Country_encoded p00u_75 and Country_encoded Latitude and p90_1200 Latitude and p00_1200 Latitude and p10_1200 Latitude and p90u_1200 Latitude and p00u_1200 Latitude and p10u_1200 Latitude and p00r_1200 Latitude and p10r_1200 Latitude and p90_30 Latitude and p00_30 Latitude and p10_30 Latitude and p90r_30 Latitude and p00r_30 Latitude and p10r_30 Latitude and p90_75 Latitude and p10_75 Latitude and p90r_75 Latitude and p00r_75 Latitude and p10r_75 Latitude and p90_150 Latitude and p00_150 Latitude and p10_150 Latitude and p90u_150 Latitude and p10u_150 Latitude and p90r_150 Latitude and p00r_150 Latitude and p10r_150 Latitude and p90_600 Latitude and p00_600 Latitude and p10_600 Latitude and p90u_600 Latitude and p10u_600 Latitude and p90r_600 Latitude and p00r_600 Latitude and p10r_600 Latitude and p90_300 Latitude and p00_300 Latitude and p10_300 Latitude and p90u_300 Latitude and p00u_300 Latitude and p10u_300 Latitude and p90r_300 Latitude and p00r_300 Latitude and p10r_300 p90_1200 and p00_1200 p90_1200 and p10_1200 p90_1200 and p90u_1200 p90_1200 and p00u_1200 p90_1200 and p10u_1200 p90_1200 and p00r_1200 p90_1200 and p10r_1200 p90_1200 and p90_30 p90_1200 and p00_30 p90_1200 and p10_30 p90_1200 and p90r_30 p90_1200 and p00r_30 p90_1200 and p10r_30 p90_1200 and p90_75 p90_1200 and p10_75 p90_1200 and p90r_75 p90_1200 and p00r_75 p90_1200 and p10r_75 p90_1200 and p90_150 p90_1200 and p00_150 p90_1200 and p10_150 p90_1200 and p90u_150 p90_1200 and p10u_150 p90_1200 and p90r_150 p90_1200 and p00r_150 p90_1200 and p10r_150 p90_1200 and p90_600 p90_1200 and p00_600 p90_1200 and p10_600 p90_1200 and p90u_600 p90_1200 and p10u_600 p90_1200 and p90r_600 p90_1200 and p00r_600 p90_1200 and p10r_600 p90_1200 and p90_300 p90_1200 and p00_300 p90_1200 and p10_300 p90_1200 and p90u_300 p90_1200 and p00u_300 p90_1200 and p10u_300 p90_1200 and p90r_300 p90_1200 and p00r_300 p90_1200 and p10r_300 p00_1200 and p10_1200 p00_1200 and p90u_1200 p00_1200 and p00u_1200 p00_1200 and p10u_1200 p00_1200 and p00r_1200 p00_1200 and p10r_1200 p00_1200 and p90_30 p00_1200 and p00_30 p00_1200 and p10_30 p00_1200 and p90r_30 p00_1200 and p00r_30 p00_1200 and p10r_30 p00_1200 and p90_75 p00_1200 and p10_75 p00_1200 and p90r_75 p00_1200 and p00r_75 p00_1200 and p10r_75 p00_1200 and p90_150 p00_1200 and p00_150 p00_1200 and p10_150 p00_1200 and p90u_150 p00_1200 and p10u_150 p00_1200 and p90r_150 p00_1200 and p00r_150 p00_1200 and p10r_150 p00_1200 and p90_600 p00_1200 and p00_600 p00_1200 and p10_600 p00_1200 and p90u_600 p00_1200 and p10u_600 p00_1200 and p90r_600 p00_1200 and p00r_600 p00_1200 and p10r_600 p00_1200 and p90_300 p00_1200 and p00_300 p00_1200 and p10_300 p00_1200 and p90u_300 p00_1200 and p00u_300 p00_1200 and p10u_300 p00_1200 and p90r_300 p00_1200 and p00r_300 p00_1200 and p10r_300 p10_1200 and p90u_1200 p10_1200 and p00u_1200 p10_1200 and p10u_1200 p10_1200 and p00r_1200 p10_1200 and p10r_1200 p10_1200 and p90_30 p10_1200 and p00_30 p10_1200 and p10_30 p10_1200 and p90r_30 p10_1200 and p00r_30 p10_1200 and p10r_30 p10_1200 and p90_75 p10_1200 and p10_75 p10_1200 and p90r_75 p10_1200 and p00r_75 p10_1200 and p10r_75 p10_1200 and p90_150 p10_1200 and p00_150 p10_1200 and p10_150 p10_1200 and p90u_150 p10_1200 and p10u_150 p10_1200 and p90r_150 p10_1200 and p00r_150 p10_1200 and p10r_150 p10_1200 and p90_600 p10_1200 and p00_600 p10_1200 and p10_600 p10_1200 and p90u_600 p10_1200 and p10u_600 p10_1200 and p90r_600 p10_1200 and p00r_600 p10_1200 and p10r_600 p10_1200 and p90_300 p10_1200 and p00_300 p10_1200 and p10_300 p10_1200 and p90u_300 p10_1200 and p00u_300 p10_1200 and p10u_300 p10_1200 and p90r_300 p10_1200 and p00r_300 p10_1200 and p10r_300 p90u_1200 and p00u_1200 p90u_1200 and p10u_1200 p90u_1200 and p00r_1200 p90u_1200 and p10r_1200 p90u_1200 and p90_30 p90u_1200 and p00_30 p90u_1200 and p10_30 p90u_1200 and p90r_30 p90u_1200 and p00r_30 p90u_1200 and p10r_30 p90u_1200 and p90_75 p90u_1200 and p10_75 p90u_1200 and p90r_75 p90u_1200 and p00r_75 p90u_1200 and p10r_75 p90u_1200 and p90_150 p90u_1200 and p00_150 p90u_1200 and p10_150 p90u_1200 and p90u_150 p90u_1200 and p10u_150 p90u_1200 and p90r_150 p90u_1200 and p00r_150 p90u_1200 and p10r_150 p90u_1200 and p90_600 p90u_1200 and p00_600 p90u_1200 and p10_600 p90u_1200 and p90u_600 p90u_1200 and p10u_600 p90u_1200 and p90r_600 p90u_1200 and p00r_600 p90u_1200 and p10r_600 p90u_1200 and p90_300 p90u_1200 and p00_300 p90u_1200 and p10_300 p90u_1200 and p90u_300 p90u_1200 and p00u_300 p90u_1200 and p10u_300 p90u_1200 and p90r_300 p90u_1200 and p00r_300 p90u_1200 and p10r_300 p00u_1200 and p10u_1200 p00u_1200 and p00r_1200 p00u_1200 and p10r_1200 p00u_1200 and p90_30 p00u_1200 and p00_30 p00u_1200 and p10_30 p00u_1200 and p90r_30 p00u_1200 and p00r_30 p00u_1200 and p10r_30 p00u_1200 and p90_75 p00u_1200 and p10_75 p00u_1200 and p90r_75 p00u_1200 and p00r_75 p00u_1200 and p10r_75 p00u_1200 and p90_150 p00u_1200 and p00_150 p00u_1200 and p10_150 p00u_1200 and p90u_150 p00u_1200 and p10u_150 p00u_1200 and p90r_150 p00u_1200 and p00r_150 p00u_1200 and p10r_150 p00u_1200 and p90_600 p00u_1200 and p00_600 p00u_1200 and p10_600 p00u_1200 and p90u_600 p00u_1200 and p10u_600 p00u_1200 and p90r_600 p00u_1200 and p00r_600 p00u_1200 and p10r_600 p00u_1200 and p90_300 p00u_1200 and p00_300 p00u_1200 and p10_300 p00u_1200 and p90u_300 p00u_1200 and p00u_300 p00u_1200 and p10u_300 p00u_1200 and p90r_300 p00u_1200 and p00r_300 p00u_1200 and p10r_300 p10u_1200 and p00r_1200 p10u_1200 and p10r_1200 p10u_1200 and p90_30 p10u_1200 and p00_30 p10u_1200 and p10_30 p10u_1200 and p90r_30 p10u_1200 and p00r_30 p10u_1200 and p10r_30 p10u_1200 and p90_75 p10u_1200 and p10_75 p10u_1200 and p90r_75 p10u_1200 and p00r_75 p10u_1200 and p10r_75 p10u_1200 and p90_150 p10u_1200 and p00_150 p10u_1200 and p10_150 p10u_1200 and p90u_150 p10u_1200 and p10u_150 p10u_1200 and p90r_150 p10u_1200 and p00r_150 p10u_1200 and p10r_150 p10u_1200 and p90_600 p10u_1200 and p00_600 p10u_1200 and p10_600 p10u_1200 and p90u_600 p10u_1200 and p10u_600 p10u_1200 and p90r_600 p10u_1200 and p00r_600 p10u_1200 and p10r_600 p10u_1200 and p90_300 p10u_1200 and p00_300 p10u_1200 and p10_300 p10u_1200 and p90u_300 p10u_1200 and p00u_300 p10u_1200 and p10u_300 p10u_1200 and p90r_300 p10u_1200 and p00r_300 p00r_1200 and p10r_1200 p00r_1200 and p90_30 p00r_1200 and p00_30 p00r_1200 and p10_30 p00r_1200 and p90r_30 p00r_1200 and p00r_30 p00r_1200 and p10r_30 p00r_1200 and p90_75 p00r_1200 and p10_75 p00r_1200 and p90r_75 p00r_1200 and p00r_75 p00r_1200 and p10r_75 p00r_1200 and p90_150 p00r_1200 and p00_150 p00r_1200 and p10_150 p00r_1200 and p90u_150 p00r_1200 and p10u_150 p00r_1200 and p90r_150 p00r_1200 and p00r_150 p00r_1200 and p10r_150 p00r_1200 and p90_600 p00r_1200 and p00_600 p00r_1200 and p10_600 p00r_1200 and p90u_600 p00r_1200 and p10u_600 p00r_1200 and p90r_600 p00r_1200 and p00r_600 p00r_1200 and p10r_600 p00r_1200 and p90_300 p00r_1200 and p00_300 p00r_1200 and p10_300 p00r_1200 and p90u_300 p00r_1200 and p00u_300 p00r_1200 and p10u_300 p00r_1200 and p90r_300 p00r_1200 and p00r_300 p00r_1200 and p10r_300 p10r_1200 and p90_30 p10r_1200 and p00_30 p10r_1200 and p10_30 p10r_1200 and p90r_30 p10r_1200 and p00r_30 p10r_1200 and p10r_30 p10r_1200 and p90_75 p10r_1200 and p10_75 p10r_1200 and p90r_75 p10r_1200 and p00r_75 p10r_1200 and p10r_75 p10r_1200 and p90_150 p10r_1200 and p00_150 p10r_1200 and p10_150 p10r_1200 and p90u_150 p10r_1200 and p10u_150 p10r_1200 and p90r_150 p10r_1200 and p00r_150 p10r_1200 and p10r_150 p10r_1200 and p90_600 p10r_1200 and p00_600 p10r_1200 and p10_600 p10r_1200 and p90u_600 p10r_1200 and p10u_600 p10r_1200 and p90r_600 p10r_1200 and p00r_600 p10r_1200 and p10r_600 p10r_1200 and p90_300 p10r_1200 and p00_300 p10r_1200 and p10_300 p10r_1200 and p90u_300 p10r_1200 and p00u_300 p10r_1200 and p10u_300 p10r_1200 and p90r_300 p10r_1200 and p00r_300 p10r_1200 and p10r_300 p90_30 and p00_30 p90_30 and p10_30 p90_30 and p90r_30 p90_30 and p00r_30 p90_30 and p10r_30 p90_30 and p90_75 p90_30 and p10_75 p90_30 and p90r_75 p90_30 and p00r_75 p90_30 and p10r_75 p90_30 and p90_150 p90_30 and p00_150 p90_30 and p10_150 p90_30 and p90u_150 p90_30 and p10u_150 p90_30 and p90r_150 p90_30 and p00r_150 p90_30 and p10r_150 p90_30 and p90_600 p90_30 and p00_600 p90_30 and p10_600 p90_30 and p90u_600 p90_30 and p10u_600 p90_30 and p90r_600 p90_30 and p00r_600 p90_30 and p10r_600 p90_30 and p90_300 p90_30 and p00_300 p90_30 and p10_300 p90_30 and p90u_300 p90_30 and p00u_300 p90_30 and p10u_300 p90_30 and p90r_300 p90_30 and p00r_300 p90_30 and p10r_300 p00_30 and p10_30 p00_30 and p90r_30 p00_30 and p00r_30 p00_30 and p10r_30 p00_30 and p90_75 p00_30 and p10_75 p00_30 and p90r_75 p00_30 and p00r_75 p00_30 and p10r_75 p00_30 and p90_150 p00_30 and p00_150 p00_30 and p10_150 p00_30 and p90u_150 p00_30 and p10u_150 p00_30 and p90r_150 p00_30 and p00r_150 p00_30 and p10r_150 p00_30 and p90_600 p00_30 and p00_600 p00_30 and p10_600 p00_30 and p90u_600 p00_30 and p10u_600 p00_30 and p90r_600 p00_30 and p00r_600 p00_30 and p10r_600 p00_30 and p90_300 p00_30 and p00_300 p00_30 and p10_300 p00_30 and p90u_300 p00_30 and p00u_300 p00_30 and p10u_300 p00_30 and p90r_300 p00_30 and p00r_300 p00_30 and p10r_300 p10_30 and p90r_30 p10_30 and p00r_30 p10_30 and p10r_30 p10_30 and p90_75 p10_30 and p10_75 p10_30 and p90r_75 p10_30 and p00r_75 p10_30 and p10r_75 p10_30 and p90_150 p10_30 and p00_150 p10_30 and p10_150 p10_30 and p90u_150 p10_30 and p10u_150 p10_30 and p90r_150 p10_30 and p00r_150 p10_30 and p10r_150 p10_30 and p90_600 p10_30 and p00_600 p10_30 and p10_600 p10_30 and p90u_600 p10_30 and p10u_600 p10_30 and p90r_600 p10_30 and p00r_600 p10_30 and p10r_600 p10_30 and p90_300 p10_30 and p00_300 p10_30 and p10_300 p10_30 and p90u_300 p10_30 and p00u_300 p10_30 and p10u_300 p10_30 and p90r_300 p10_30 and p00r_300 p10_30 and p10r_300 p90r_30 and p00r_30 p90r_30 and p10r_30 p90r_30 and p90_75 p90r_30 and p10_75 p90r_30 and p90r_75 p90r_30 and p00r_75 p90r_30 and p10r_75 p90r_30 and p90_150 p90r_30 and p00_150 p90r_30 and p10_150 p90r_30 and p90u_150 p90r_30 and p10u_150 p90r_30 and p90r_150 p90r_30 and p00r_150 p90r_30 and p10r_150 p90r_30 and p90_600 p90r_30 and p00_600 p90r_30 and p10_600 p90r_30 and p90u_600 p90r_30 and p10u_600 p90r_30 and p90r_600 p90r_30 and p00r_600 p90r_30 and p10r_600 p90r_30 and p90_300 p90r_30 and p00_300 p90r_30 and p10_300 p90r_30 and p90u_300 p90r_30 and p00u_300 p90r_30 and p10u_300 p90r_30 and p90r_300 p90r_30 and p00r_300 p90r_30 and p10r_300 p00r_30 and p10r_30 p00r_30 and p90_75 p00r_30 and p10_75 p00r_30 and p90r_75 p00r_30 and p00r_75 p00r_30 and p10r_75 p00r_30 and p90_150 p00r_30 and p00_150 p00r_30 and p10_150 p00r_30 and p90u_150 p00r_30 and p10u_150 p00r_30 and p90r_150 p00r_30 and p00r_150 p00r_30 and p10r_150 p00r_30 and p90_600 p00r_30 and p00_600 p00r_30 and p10_600 p00r_30 and p90u_600 p00r_30 and p10u_600 p00r_30 and p90r_600 p00r_30 and p00r_600 p00r_30 and p10r_600 p00r_30 and p90_300 p00r_30 and p00_300 p00r_30 and p10_300 p00r_30 and p90u_300 p00r_30 and p00u_300 p00r_30 and p10u_300 p00r_30 and p90r_300 p00r_30 and p00r_300 p00r_30 and p10r_300 p10r_30 and p90_75 p10r_30 and p10_75 p10r_30 and p90r_75 p10r_30 and p00r_75 p10r_30 and p10r_75 p10r_30 and p90_150 p10r_30 and p00_150 p10r_30 and p10_150 p10r_30 and p90u_150 p10r_30 and p10u_150 p10r_30 and p90r_150 p10r_30 and p00r_150 p10r_30 and p10r_150 p10r_30 and p90_600 p10r_30 and p00_600 p10r_30 and p10_600 p10r_30 and p90u_600 p10r_30 and p10u_600 p10r_30 and p90r_600 p10r_30 and p00r_600 p10r_30 and p10r_600 p10r_30 and p90_300 p10r_30 and p00_300 p10r_30 and p10_300 p10r_30 and p90u_300 p10r_30 and p00u_300 p10r_30 and p10u_300 p10r_30 and p90r_300 p10r_30 and p00r_300 p10r_30 and p10r_300 p90_75 and p10_75 p90_75 and p90r_75 p90_75 and p00r_75 p90_75 and p10r_75 p90_75 and p90_150 p90_75 and p00_150 p90_75 and p10_150 p90_75 and p90u_150 p90_75 and p10u_150 p90_75 and p90r_150 p90_75 and p00r_150 p90_75 and p10r_150 p90_75 and p90_600 p90_75 and p00_600 p90_75 and p10_600 p90_75 and p90u_600 p90_75 and p10u_600 p90_75 and p90r_600 p90_75 and p00r_600 p90_75 and p10r_600 p90_75 and p90_300 p90_75 and p00_300 p90_75 and p10_300 p90_75 and p90u_300 p90_75 and p00u_300 p90_75 and p10u_300 p90_75 and p90r_300 p90_75 and p00r_300 p90_75 and p10r_300 p10_75 and p90r_75 p10_75 and p00r_75 p10_75 and p10r_75 p10_75 and p90_150 p10_75 and p00_150 p10_75 and p10_150 p10_75 and p90u_150 p10_75 and p10u_150 p10_75 and p90r_150 p10_75 and p00r_150 p10_75 and p10r_150 p10_75 and p90_600 p10_75 and p00_600 p10_75 and p10_600 p10_75 and p90u_600 p10_75 and p10u_600 p10_75 and p90r_600 p10_75 and p00r_600 p10_75 and p10r_600 p10_75 and p90_300 p10_75 and p00_300 p10_75 and p10_300 p10_75 and p90u_300 p10_75 and p00u_300 p10_75 and p10u_300 p10_75 and p90r_300 p10_75 and p00r_300 p10_75 and p10r_300 p90r_75 and p00r_75 p90r_75 and p10r_75 p90r_75 and p90_150 p90r_75 and p00_150 p90r_75 and p10_150 p90r_75 and p90u_150 p90r_75 and p10u_150 p90r_75 and p90r_150 p90r_75 and p00r_150 p90r_75 and p10r_150 p90r_75 and p90_600 p90r_75 and p00_600 p90r_75 and p10_600 p90r_75 and p90u_600 p90r_75 and p10u_600 p90r_75 and p90r_600 p90r_75 and p00r_600 p90r_75 and p10r_600 p90r_75 and p90_300 p90r_75 and p00_300 p90r_75 and p10_300 p90r_75 and p90u_300 p90r_75 and p00u_300 p90r_75 and p10u_300 p90r_75 and p90r_300 p90r_75 and p00r_300 p90r_75 and p10r_300 p00r_75 and p10r_75 p00r_75 and p90_150 p00r_75 and p00_150 p00r_75 and p10_150 p00r_75 and p90u_150 p00r_75 and p10u_150 p00r_75 and p90r_150 p00r_75 and p00r_150 p00r_75 and p10r_150 p00r_75 and p90_600 p00r_75 and p00_600 p00r_75 and p10_600 p00r_75 and p90u_600 p00r_75 and p10u_600 p00r_75 and p90r_600 p00r_75 and p00r_600 p00r_75 and p10r_600 p00r_75 and p90_300 p00r_75 and p00_300 p00r_75 and p10_300 p00r_75 and p90u_300 p00r_75 and p00u_300 p00r_75 and p10u_300 p00r_75 and p90r_300 p00r_75 and p00r_300 p00r_75 and p10r_300 p10r_75 and p90_150 p10r_75 and p00_150 p10r_75 and p10_150 p10r_75 and p90u_150 p10r_75 and p10u_150 p10r_75 and p90r_150 p10r_75 and p00r_150 p10r_75 and p10r_150 p10r_75 and p90_600 p10r_75 and p00_600 p10r_75 and p10_600 p10r_75 and p90u_600 p10r_75 and p10u_600 p10r_75 and p90r_600 p10r_75 and p00r_600 p10r_75 and p10r_600 p10r_75 and p90_300 p10r_75 and p00_300 p10r_75 and p10_300 p10r_75 and p90u_300 p10r_75 and p00u_300 p10r_75 and p10u_300 p10r_75 and p90r_300 p10r_75 and p00r_300 p10r_75 and p10r_300 p90_150 and p00_150 p90_150 and p10_150 p90_150 and p90u_150 p90_150 and p10u_150 p90_150 and p90r_150 p90_150 and p00r_150 p90_150 and p10r_150 p90_150 and p90_600 p90_150 and p00_600 p90_150 and p10_600 p90_150 and p90u_600 p90_150 and p10u_600 p90_150 and p90r_600 p90_150 and p00r_600 p90_150 and p10r_600 p90_150 and p90_300 p90_150 and p00_300 p90_150 and p10_300 p90_150 and p90u_300 p90_150 and p00u_300 p90_150 and p10u_300 p90_150 and p90r_300 p90_150 and p00r_300 p90_150 and p10r_300 p00_150 and p10_150 p00_150 and p90u_150 p00_150 and p10u_150 p00_150 and p90r_150 p00_150 and p00r_150 p00_150 and p10r_150 p00_150 and p90_600 p00_150 and p00_600 p00_150 and p10_600 p00_150 and p90u_600 p00_150 and p10u_600 p00_150 and p90r_600 p00_150 and p00r_600 p00_150 and p10r_600 p00_150 and p90_300 p00_150 and p00_300 p00_150 and p10_300 p00_150 and p90u_300 p00_150 and p00u_300 p00_150 and p10u_300 p00_150 and p90r_300 p00_150 and p00r_300 p00_150 and p10r_300 p10_150 and p90u_150 p10_150 and p10u_150 p10_150 and p90r_150 p10_150 and p00r_150 p10_150 and p10r_150 p10_150 and p90_600 p10_150 and p00_600 p10_150 and p10_600 p10_150 and p90u_600 p10_150 and p10u_600 p10_150 and p90r_600 p10_150 and p00r_600 p10_150 and p10r_600 p10_150 and p90_300 p10_150 and p00_300 p10_150 and p10_300 p10_150 and p90u_300 p10_150 and p00u_300 p10_150 and p10u_300 p10_150 and p90r_300 p10_150 and p00r_300 p10_150 and p10r_300 p90u_150 and p10u_150 p90u_150 and p90r_150 p90u_150 and p00r_150 p90u_150 and p10r_150 p90u_150 and p90_600 p90u_150 and p00_600 p90u_150 and p10_600 p90u_150 and p90u_600 p90u_150 and p10u_600 p90u_150 and p90r_600 p90u_150 and p00r_600 p90u_150 and p10r_600 p90u_150 and p90_300 p90u_150 and p00_300 p90u_150 and p10_300 p90u_150 and p90u_300 p90u_150 and p00u_300 p90u_150 and p10u_300 p90u_150 and p90r_300 p90u_150 and p00r_300 p90u_150 and p10r_300 p10u_150 and p90r_150 p10u_150 and p00r_150 p10u_150 and p10r_150 p10u_150 and p90_600 p10u_150 and p00_600 p10u_150 and p10_600 p10u_150 and p90u_600 p10u_150 and p10u_600 p10u_150 and p90r_600 p10u_150 and p00r_600 p10u_150 and p10r_600 p10u_150 and p90_300 p10u_150 and p00_300 p10u_150 and p10_300 p10u_150 and p90u_300 p10u_150 and p00u_300 p10u_150 and p10u_300 p10u_150 and p90r_300 p10u_150 and p00r_300 p10u_150 and p10r_300 p90r_150 and p00r_150 p90r_150 and p10r_150 p90r_150 and p90_600 p90r_150 and p00_600 p90r_150 and p10_600 p90r_150 and p90u_600 p90r_150 and p10u_600 p90r_150 and p90r_600 p90r_150 and p00r_600 p90r_150 and p10r_600 p90r_150 and p90_300 p90r_150 and p00_300 p90r_150 and p10_300 p90r_150 and p90u_300 p90r_150 and p00u_300 p90r_150 and p10u_300 p90r_150 and p90r_300 p90r_150 and p00r_300 p90r_150 and p10r_300 p00r_150 and p10r_150 p00r_150 and p90_600 p00r_150 and p00_600 p00r_150 and p10_600 p00r_150 and p90u_600 p00r_150 and p10u_600 p00r_150 and p90r_600 p00r_150 and p00r_600 p00r_150 and p10r_600 p00r_150 and p90_300 p00r_150 and p00_300 p00r_150 and p10_300 p00r_150 and p90u_300 p00r_150 and p00u_300 p00r_150 and p10u_300 p00r_150 and p90r_300 p00r_150 and p00r_300 p00r_150 and p10r_300 p10r_150 and p90_600 p10r_150 and p00_600 p10r_150 and p10_600 p10r_150 and p90u_600 p10r_150 and p10u_600 p10r_150 and p90r_600 p10r_150 and p00r_600 p10r_150 and p10r_600 p10r_150 and p90_300 p10r_150 and p00_300 p10r_150 and p10_300 p10r_150 and p90u_300 p10r_150 and p00u_300 p10r_150 and p10u_300 p10r_150 and p90r_300 p10r_150 and p00r_300 p10r_150 and p10r_300 p90_600 and p00_600 p90_600 and p10_600 p90_600 and p90u_600 p90_600 and p10u_600 p90_600 and p90r_600 p90_600 and p00r_600 p90_600 and p10r_600 p90_600 and p90_300 p90_600 and p00_300 p90_600 and p10_300 p90_600 and p90u_300 p90_600 and p00u_300 p90_600 and p10u_300 p90_600 and p90r_300 p90_600 and p00r_300 p90_600 and p10r_300 p00_600 and p10_600 p00_600 and p90u_600 p00_600 and p10u_600 p00_600 and p90r_600 p00_600 and p00r_600 p00_600 and p10r_600 p00_600 and p90_300 p00_600 and p00_300 p00_600 and p10_300 p00_600 and p90u_300 p00_600 and p00u_300 p00_600 and p10u_300 p00_600 and p90r_300 p00_600 and p00r_300 p00_600 and p10r_300 p10_600 and p90u_600 p10_600 and p10u_600 p10_600 and p90r_600 p10_600 and p00r_600 p10_600 and p10r_600 p10_600 and p90_300 p10_600 and p00_300 p10_600 and p10_300 p10_600 and p90u_300 p10_600 and p00u_300 p10_600 and p10u_300 p10_600 and p90r_300 p10_600 and p00r_300 p10_600 and p10r_300 p90u_600 and p10u_600 p90u_600 and p90r_600 p90u_600 and p00r_600 p90u_600 and p10r_600 p90u_600 and p90_300 p90u_600 and p00_300 p90u_600 and p10_300 p90u_600 and p90u_300 p90u_600 and p00u_300 p90u_600 and p10u_300 p90u_600 and p90r_300 p90u_600 and p00r_300 p90u_600 and p10r_300 p10u_600 and p90r_600 p10u_600 and p00r_600 p10u_600 and p10r_600 p10u_600 and p90_300 p10u_600 and p00_300 p10u_600 and p10_300 p10u_600 and p90u_300 p10u_600 and p00u_300 p10u_600 and p10u_300 p10u_600 and p90r_300 p10u_600 and p00r_300 p10u_600 and p10r_300 p90r_600 and p00r_600 p90r_600 and p10r_600 p90r_600 and p90_300 p90r_600 and p00_300 p90r_600 and p10_300 p90r_600 and p90u_300 p90r_600 and p00u_300 p90r_600 and p10u_300 p90r_600 and p90r_300 p90r_600 and p00r_300 p90r_600 and p10r_300 p00r_600 and p10r_600 p00r_600 and p90_300 p00r_600 and p00_300 p00r_600 and p10_300 p00r_600 and p90u_300 p00r_600 and p00u_300 p00r_600 and p10u_300 p00r_600 and p90r_300 p10r_600 and p90_300 p10r_600 and p00_300 p10r_600 and p10_300 p10r_600 and p90u_300 p10r_600 and p00u_300 p10r_600 and p10u_300 p10r_600 and p90r_300 p10r_600 and p00r_300 p10r_600 and p10r_300 p90_300 and p00_300 p90_300 and p10_300 p90_300 and p90u_300 p90_300 and p00u_300 p90_300 and p10u_300 p90_300 and p90r_300 p90_300 and p00r_300 p90_300 and p10r_300 p00_300 and p10_300 p00_300 and p90u_300 p00_300 and p00u_300 p00_300 and p10u_300 p00_300 and p90r_300 p00_300 and p00r_300 p00_300 and p10r_300 p10_300 and p90u_300 p10_300 and p10u_300 p10_300 and p90r_300 p10_300 and p00r_300 p10_300 and p10r_300 p90u_300 and p00u_300 p90u_300 and p10u_300 p90u_300 and p90r_300 p90u_300 and p00r_300 p90u_300 and p10r_300 p00u_300 and p10u_300 p00u_300 and p90r_300 p00u_300 and p00r_300 p00u_300 and p10r_300 p10u_300 and p90r_300 p10u_300 and p00r_300 p10u_300 and p10r_300 p90r_300 and p00r_300 p90r_300 and p10r_300 p00r_300 and p10r_300 p10u_1200 and p10r_300 p00r_600 and p00r_300 p00r_600 and p10r_300 p10_300 and p00u_300 Latitude and p90u_30 Latitude and p00u_30 Latitude and p10u_30 Latitude and p00_75 Latitude and p00u_150 p90_1200 and p90u_30 p90_1200 and p00u_30 p90_1200 and p10u_30 p90_1200 and p00u_600 p00_1200 and p90r_1200 p00_1200 and p10u_30 p00_1200 and p00u_150 p10_1200 and p90r_1200 p10_1200 and p00u_30 p10_1200 and p10u_30 p10_1200 and p00u_150 p10_1200 and p00u_600 p90u_1200 and p10u_30 p90u_1200 and p00_75 p90u_1200 and p00u_150 p00u_1200 and p90u_30 p00u_1200 and p00u_30 p00u_1200 and p10u_30 p00u_1200 and p00u_150 p10u_1200 and p90r_1200 p10u_1200 and p90u_30 p10u_1200 and p10u_30 p10u_1200 and p00_75 p10u_1200 and p00u_150 p10u_1200 and p00u_600 p00r_1200 and p90u_30 p00r_1200 and p00u_30 p00r_1200 and p10u_30 p00r_1200 and p00u_150 p10r_1200 and p90u_30 p10r_1200 and p00u_30 p10r_1200 and p10u_30 p10r_1200 and p00u_150 p90_30 and p10u_30 p90_30 and p00u_150 p90_30 and p00u_600 p00_30 and p00u_30 p00_30 and p10u_30 p00_30 and p00u_150 p10_30 and p00_75 p10_30 and p00u_150 p90r_30 and p00_75 p90r_30 and p00u_150 p00r_30 and p00u_150 p10r_30 and p00_75 p90_75 and p00u_150 p10_75 and p00u_150 p90r_75 and p00u_150 p90r_75 and p00u_600 p10r_75 and p00u_150 p90_150 and p00u_150 p00_150 and p00u_600 p90u_150 and p00u_150 p90r_150 and p00u_600 Latitude and p90r_1200 Latitude and p00u_600 p90_1200 and p90r_1200 p90_1200 and p00_75 p90_1200 and p00u_150 p00_1200 and p90u_30 p00_1200 and p00u_30 p00_1200 and p00_75 p00_1200 and p00u_600 p10_1200 and p90u_30 p10_1200 and p00_75 p90u_1200 and p90r_1200 p90u_1200 and p90u_30 p90u_1200 and p00u_30 p90u_1200 and p00u_600 p00u_1200 and p90r_1200 p00u_1200 and p00_75 p00u_1200 and p00u_600 p10u_1200 and p00u_30 p90r_1200 and p00r_1200 p90r_1200 and p10r_1200 p90r_1200 and p90_30 p90r_1200 and p00_30 p90r_1200 and p10_30 p90r_1200 and p90r_30 p90r_1200 and p00r_30 p90r_1200 and p10r_30 p90r_1200 and p90_75 p90r_1200 and p10_75 p90r_1200 and p90r_75 p90r_1200 and p00r_75 p90r_1200 and p10r_75 p90r_1200 and p90_150 p90r_1200 and p00_150 p90r_1200 and p10_150 p90r_1200 and p90u_150 p90r_1200 and p10u_150 p90r_1200 and p90r_150 p90r_1200 and p00r_150 p90r_1200 and p10r_150 p90r_1200 and p90_600 p90r_1200 and p00_600 p90r_1200 and p10_600 p90r_1200 and p90u_600 p90r_1200 and p10u_600 p90r_1200 and p90r_600 p90r_1200 and p00r_600 p90r_1200 and p10r_600 p90r_1200 and p90_300 p90r_1200 and p00_300 p90r_1200 and p10_300 p90r_1200 and p90u_300 p90r_1200 and p00u_300 p90r_1200 and p10u_300 p90r_1200 and p90r_300 p90r_1200 and p00r_300 p90r_1200 and p10r_300 p00r_1200 and p00_75 p00r_1200 and p00u_600 p10r_1200 and p00_75 p10r_1200 and p00u_600 p90_30 and p90u_30 p90_30 and p00u_30 p90_30 and p00_75 p00_30 and p90u_30 p00_30 and p00_75 p00_30 and p00u_600 p10_30 and p90u_30 p10_30 and p00u_30 p10_30 and p10u_30 p10_30 and p00u_600 p90u_30 and p90r_30 p90u_30 and p00r_30 p90u_30 and p10r_30 p90u_30 and p90_75 p90u_30 and p10_75 p90u_30 and p90r_75 p90u_30 and p00r_75 p90u_30 and p10r_75 p90u_30 and p90_150 p90u_30 and p00_150 p90u_30 and p10_150 p90u_30 and p90u_150 p90u_30 and p10u_150 p90u_30 and p90r_150 p90u_30 and p00r_150 p90u_30 and p10r_150 p90u_30 and p90_600 p90u_30 and p00_600 p90u_30 and p10_600 p90u_30 and p90u_600 p90u_30 and p10u_600 p90u_30 and p90r_600 p90u_30 and p00r_600 p90u_30 and p10r_600 p90u_30 and p90_300 p90u_30 and p00_300 p90u_30 and p10_300 p90u_30 and p90u_300 p90u_30 and p00u_300 p90u_30 and p10u_300 p90u_30 and p90r_300 p90u_30 and p00r_300 p90u_30 and p10r_300 p00u_30 and p90r_30 p00u_30 and p00r_30 p00u_30 and p10r_30 p00u_30 and p90_75 p00u_30 and p10_75 p00u_30 and p90r_75 p00u_30 and p00r_75 p00u_30 and p10r_75 p00u_30 and p90_150 p00u_30 and p00_150 p00u_30 and p10_150 p00u_30 and p90u_150 p00u_30 and p10u_150 p00u_30 and p90r_150 p00u_30 and p00r_150 p00u_30 and p10r_150 p00u_30 and p90_600 p00u_30 and p00_600 p00u_30 and p10_600 p00u_30 and p90u_600 p00u_30 and p10u_600 p00u_30 and p90r_600 p00u_30 and p00r_600 p00u_30 and p10r_600 p00u_30 and p90_300 p00u_30 and p00_300 p00u_30 and p10_300 p00u_30 and p90u_300 p00u_30 and p00u_300 p00u_30 and p10u_300 p00u_30 and p90r_300 p00u_30 and p00r_300 p00u_30 and p10r_300 p10u_30 and p90r_30 p10u_30 and p00r_30 p10u_30 and p10r_30 p10u_30 and p90_75 p10u_30 and p10_75 p10u_30 and p90r_75 p10u_30 and p00r_75 p10u_30 and p10r_75 p10u_30 and p90_150 p10u_30 and p00_150 p10u_30 and p10_150 p10u_30 and p90u_150 p10u_30 and p10u_150 p10u_30 and p90r_150 p10u_30 and p00r_150 p10u_30 and p10r_150 p10u_30 and p90_600 p10u_30 and p00_600 p10u_30 and p10_600 p10u_30 and p90u_600 p10u_30 and p10u_600 p10u_30 and p90r_600 p10u_30 and p00r_600 p10u_30 and p10r_600 p10u_30 and p90_300 p10u_30 and p00_300 p10u_30 and p10_300 p10u_30 and p90u_300 p10u_30 and p00u_300 p10u_30 and p10u_300 p10u_30 and p90r_300 p10u_30 and p00r_300 p10u_30 and p10r_300 p90r_30 and p00u_600 p00r_30 and p00_75 p00r_30 and p00u_600 p10r_30 and p00u_150 p10r_30 and p00u_600 p90_75 and p00_75 p90_75 and p00u_600 p00_75 and p10_75 p00_75 and p90r_75 p00_75 and p00r_75 p00_75 and p10r_75 p00_75 and p90_150 p00_75 and p00_150 p00_75 and p10_150 p00_75 and p90u_150 p00_75 and p10u_150 p00_75 and p90r_150 p00_75 and p00r_150 p00_75 and p10r_150 p00_75 and p90_600 p00_75 and p00_600 p00_75 and p10_600 p00_75 and p90u_600 p00_75 and p10u_600 p00_75 and p90r_600 p00_75 and p00r_600 p00_75 and p10r_600 p00_75 and p90_300 p00_75 and p00_300 p00_75 and p10_300 p00_75 and p90u_300 p00_75 and p00u_300 p00_75 and p10u_300 p00_75 and p90r_300 p00_75 and p00r_300 p00_75 and p10r_300 p10_75 and p00u_600 p00r_75 and p00u_150 p00r_75 and p00u_600 p10r_75 and p00u_600 p90_150 and p00u_600 p00_150 and p00u_150 p10_150 and p00u_150 p10_150 and p00u_600 p90u_150 and p00u_600 p00u_150 and p10u_150 p00u_150 and p90r_150 p00u_150 and p00r_150 p00u_150 and p10r_150 p00u_150 and p90_600 p00u_150 and p00_600 p00u_150 and p10_600 p00u_150 and p90u_600 p00u_150 and p10u_600 p00u_150 and p90r_600 p00u_150 and p00r_600 p00u_150 and p10r_600 p00u_150 and p90_300 p00u_150 and p00_300 p00u_150 and p10_300 p00u_150 and p90u_300 p00u_150 and p00u_300 p00u_150 and p10u_300 p00u_150 and p90r_300 p00u_150 and p00r_300 p00u_150 and p10r_300 p10u_150 and p00u_600 p00r_150 and p00u_600 p10r_150 and p00u_600 p90_600 and p00u_600 p00_600 and p00u_600 p10_600 and p00u_600 p90u_600 and p00u_600 p00u_600 and p10u_600 p00u_600 and p90r_600 p00u_600 and p00r_600 p00u_600 and p10r_600 p00u_600 and p90_300 p00u_600 and p00_300 p00u_600 and p10_300 p00u_600 and p90u_300 p00u_600 and p00u_300 p00u_600 and p10u_300 p00u_600 and p90r_300 p00u_600 and p00r_300 p00u_600 and p10r_300 Latitude and Longitude Latitude and p90u_75 Latitude and p00u_75 Latitude and p10u_75 p90_1200 and p90u_75 p90_1200 and p00u_75 p90_1200 and p10u_75 p00_1200 and p90u_75 p00_1200 and p00u_75 p00_1200 and p10u_75 p10_1200 and p90u_75 p10_1200 and p00u_75 p10_1200 and p10u_75 p90u_1200 and p90u_75 p90u_1200 and p00u_75 p90u_1200 and p10u_75 p00u_1200 and p90u_75 p00u_1200 and p00u_75 p00u_1200 and p10u_75 p10u_1200 and p90u_75 p10u_1200 and p00u_75 p10u_1200 and p10u_75 p00r_1200 and p90u_75 p00r_1200 and p00u_75 p00r_1200 and p10u_75 p10r_1200 and p90u_75 p10r_1200 and p00u_75 p10r_1200 and p10u_75 p90_30 and p90u_75 p90_30 and p00u_75 p90_30 and p10u_75 p00_30 and p90u_75 p00_30 and p00u_75 p00_30 and p10u_75 p10_30 and p90u_75 p10_30 and p00u_75 p10_30 and p10u_75 p90r_30 and p90u_75 p90r_30 and p00u_75 p90r_30 and p10u_75 p00r_30 and p90u_75 p00r_30 and p00u_75 p00r_30 and p10u_75 p10r_30 and p90u_75 p10r_30 and p00u_75 p10r_30 and p10u_75 p90_75 and p90u_75 p90_75 and p00u_75 p90_75 and p10u_75 p10_75 and p90u_75 p10_75 and p00u_75 p10_75 and p10u_75 Longitude and p90_1200 Longitude and p00_1200 Longitude and p10_1200 Longitude and p90u_1200 Longitude and p00u_1200 Longitude and p10u_1200 Longitude and p00r_1200 Longitude and p10r_1200 Longitude and p90_30 Longitude and p00_30 Longitude and p10_30 Longitude and p90r_30 Longitude and p00r_30 Longitude and p10r_30 Longitude and p90_75 Longitude and p10_75 Longitude and p90r_75 Longitude and p00r_75 Longitude and p10r_75 Longitude and p90_150 Longitude and p10_150 Longitude and p90u_150 Longitude and p10u_150 Longitude and p90r_150 Longitude and p00r_150 Longitude and p10r_150 Longitude and p90_600 Longitude and p00_600 Longitude and p10_600 Longitude and p90u_600 Longitude and p10u_600 Longitude and p90r_600 Longitude and p00r_600 Longitude and p10r_600 Longitude and p90_300 Longitude and p00_300 Longitude and p10_300 Longitude and p90u_300 Longitude and p00u_300 Longitude and p10u_300 Longitude and p90r_300 Longitude and p00r_300 Longitude and p10r_300 p90u_75 and p90r_75 p90u_75 and p00r_75 p90u_75 and p10r_75 p90u_75 and p90_150 p90u_75 and p00_150 p90u_75 and p10_150 p90u_75 and p90u_150 p90u_75 and p10u_150 p90u_75 and p90r_150 p90u_75 and p00r_150 p90u_75 and p10r_150 p90u_75 and p90_600 p90u_75 and p00_600 p90u_75 and p10_600 p90u_75 and p90u_600 p90u_75 and p10u_600 p90u_75 and p90r_600 p90u_75 and p00r_600 p90u_75 and p10r_600 p90u_75 and p90_300 p90u_75 and p00_300 p90u_75 and p10_300 p90u_75 and p90u_300 p90u_75 and p00u_300 p90u_75 and p10u_300 p90u_75 and p90r_300 p90u_75 and p00r_300 p90u_75 and p10r_300 p00u_75 and p90r_75 p00u_75 and p00r_75 p00u_75 and p10r_75 p00u_75 and p90_150 p00u_75 and p00_150 p00u_75 and p10_150 p00u_75 and p90u_150 p00u_75 and p10u_150 p00u_75 and p90r_150 p00u_75 and p00r_150 p00u_75 and p10r_150 p00u_75 and p90_600 p00u_75 and p00_600 p00u_75 and p10_600 p00u_75 and p90u_600 p00u_75 and p10u_600 p00u_75 and p90r_600 p00u_75 and p00r_600 p00u_75 and p10r_600 p00u_75 and p90_300 p00u_75 and p00_300 p00u_75 and p10_300 p00u_75 and p90u_300 p00u_75 and p00u_300 p00u_75 and p10u_300 p00u_75 and p90r_300 p00u_75 and p00r_300 p00u_75 and p10r_300 p10u_75 and p90r_75 p10u_75 and p00r_75 p10u_75 and p10r_75 p10u_75 and p90_150 p10u_75 and p00_150 p10u_75 and p10_150 p10u_75 and p90u_150 p10u_75 and p10u_150 p10u_75 and p90r_150 p10u_75 and p00r_150 p10u_75 and p10r_150 p10u_75 and p90_600 p10u_75 and p00_600 p10u_75 and p10_600 p10u_75 and p90u_600 p10u_75 and p10u_600 p10u_75 and p90r_600 p10u_75 and p00r_600 p10u_75 and p10r_600 p10u_75 and p90_300 p10u_75 and p00_300 p10u_75 and p10_300 p10u_75 and p90u_300 p10u_75 and p00u_300 p10u_75 and p10u_300 p10u_75 and p90r_300 p10u_75 and p00r_300 p10u_75 and p10r_300 Longitude and p00_150 p90r_1200 and p10u_30 p90r_1200 and p00u_150 p10u_30 and p00u_600 p90r_1200 and p90u_30 p90r_1200 and p00u_30 p90r_1200 and p00_75 p90r_1200 and p00u_600 p90u_30 and p00_75 p90u_30 and p00u_150 p90u_30 and p00u_600 p00u_30 and p00_75 p00u_30 and p00u_150 p00u_30 and p00u_600 p10u_30 and p00_75 p10u_30 and p00u_150 p00_75 and p00u_150 p00_75 and p00u_600 p00u_150 and p00u_600 Longitude and p90r_1200 Longitude and p90u_30 Longitude and p00u_30 Longitude and p00u_150 p90r_1200 and p90u_75 p90r_1200 and p00u_75 p90r_1200 and p10u_75 p90u_30 and p90u_75 p90u_30 and p00u_75 p90u_30 and p10u_75 p00u_30 and p90u_75 p00u_30 and p00u_75 p00u_30 and p10u_75 p10u_30 and p90u_75 p10u_30 and p00u_75 p10u_30 and p10u_75 p90u_75 and p00u_600 p00u_75 and p00u_150 p00u_75 and p00u_600 p10u_75 and p00u_150 Longitude and p10u_30 Longitude and p00_75 Longitude and p00u_600 p90u_75 and p00u_150 p10u_75 and p00u_600 Longitude and p90u_75 Longitude and p00u_75 Longitude and p10u_75 p90r_1200 and Country_encoded p00_75 and Country_encoded p90u_30 and Country_encoded p00u_30 and Country_encoded p10u_30 and Country_encoded p00u_600 and Country_encoded p00u_150 and Country_encoded p90_1200 and Country_encoded p00u_1200 and Country_encoded p00_300 and Country_encoded p90u_300 and Country_encoded Latitude and Country_encoded p00_1200 and Country_encoded p10_1200 and Country_encoded p90u_1200 and Country_encoded p10u_1200 and Country_encoded p00r_1200 and Country_encoded p10r_1200 and Country_encoded p90_30 and Country_encoded p00_30 and Country_encoded p10_30 and Country_encoded p00r_30 and Country_encoded p10r_30 and Country_encoded p90_75 and Country_encoded p10_75 and Country_encoded p90r_75 and Country_encoded p00r_75 and Country_encoded p10r_75 and Country_encoded p90_150 and Country_encoded p00_150 and Country_encoded p10_150 and Country_encoded p90u_150 and Country_encoded p10u_150 and Country_encoded p90r_150 and Country_encoded p00r_150 and Country_encoded p10r_150 and Country_encoded p90_600 and Country_encoded p00_600 and Country_encoded p10_600 and Country_encoded p90u_600 and Country_encoded p10u_600 and Country_encoded p90r_600 and Country_encoded p00r_600 and Country_encoded p10r_600 and Country_encoded p90_300 and Country_encoded p10_300 and Country_encoded p00u_300 and Country_encoded p10u_300 and Country_encoded p90r_300 and Country_encoded p00r_300 and Country_encoded p10r_300 and Country_encoded p90r_30 and Country_encoded Dependent variables: p90u_75 and p00u_75 p90u_75 and p10u_75 p00u_75 and p10u_75
df
| Latitude | Longitude | p90_1200 | p00_1200 | p10_1200 | p90u_1200 | p00u_1200 | p10u_1200 | p90r_1200 | p00r_1200 | ... | p90_300 | p00_300 | p10_300 | p90u_300 | p00u_300 | p10u_300 | p90r_300 | p00r_300 | p10r_300 | Country_encoded | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1.352765 | 0.251194 | -0.464402 | -0.508016 | -0.554848 | -0.593107 | -0.660152 | -0.734917 | -0.252291 | -0.282518 | ... | -1.172443 | -1.136296 | -1.125151 | -1.191514 | -1.198046 | -1.215751 | -0.738981 | -0.675829 | -0.636833 | 0.605681 |
| 1 | -0.126329 | -0.064588 | -0.774040 | -0.731805 | -0.679515 | -0.964721 | -0.953322 | -0.919337 | -0.444835 | -0.404765 | ... | -0.586885 | -0.600261 | -0.556108 | -0.716401 | -0.736024 | -0.708998 | -0.154835 | -0.193095 | -0.156917 | 0.514631 |
| 2 | -4.916056 | -0.579314 | -1.002907 | -0.916580 | -0.857975 | -1.183329 | -1.120005 | -1.079853 | -0.644420 | -0.576372 | ... | 0.414370 | 0.496365 | 0.605076 | 0.653952 | 0.779507 | 0.935261 | -0.156248 | -0.111894 | -0.068467 | -1.670572 |
| 3 | -0.469286 | -1.226995 | -0.889115 | -0.813688 | -0.764634 | -0.908713 | -0.841270 | -0.801030 | -0.714629 | -0.655143 | ... | -1.145335 | -1.094991 | -1.071174 | -1.169357 | -1.162423 | -1.166418 | -0.712229 | -0.638664 | -0.593155 | 1.060932 |
| 4 | -0.020197 | 0.018589 | 0.051419 | 0.029799 | 0.051246 | 0.176309 | 0.148003 | 0.179467 | -0.085040 | -0.085873 | ... | -0.741186 | -0.728155 | -0.685837 | -0.701982 | -0.714859 | -0.682794 | -0.559051 | -0.517095 | -0.473250 | 0.514631 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | -1.506439 | 1.501828 | 1.792834 | 1.899641 | 1.913771 | 0.839405 | 1.051898 | 1.110167 | 2.454943 | 2.384831 | ... | 1.727114 | 2.251499 | 2.276462 | 1.196198 | 1.746700 | 1.828051 | 2.090747 | 2.335818 | 2.210780 | -1.397422 |
| 272 | 0.096301 | -0.957393 | -0.854920 | -0.820254 | -0.771264 | -0.789761 | -0.786267 | -0.743154 | -0.772925 | -0.718363 | ... | 0.245594 | 0.188036 | 0.253678 | 0.620326 | 0.569365 | 0.671899 | -0.509843 | -0.477951 | -0.437206 | 1.060932 |
| 273 | -0.461599 | 1.689799 | 2.357024 | 2.340021 | 2.270520 | 2.538004 | 2.634711 | 2.644594 | 1.762702 | 1.682191 | ... | 0.566912 | 0.570582 | 0.541617 | 0.867854 | 0.941671 | 0.931923 | -0.165667 | -0.201114 | -0.199622 | -0.395870 |
| 274 | 0.461080 | 0.470339 | 0.061055 | -0.037393 | -0.131383 | -0.141744 | -0.234249 | -0.340844 | 0.257537 | 0.153308 | ... | -0.455104 | -0.551699 | -0.640980 | -0.537094 | -0.643647 | -0.744355 | -0.153133 | -0.229645 | -0.287221 | 0.878832 |
| 275 | 0.074844 | -1.154910 | -0.616189 | -0.577300 | -0.524737 | -0.479518 | -0.452401 | -0.391292 | -0.648693 | -0.600271 | ... | -0.497452 | -0.464913 | -0.420298 | -0.360175 | -0.330085 | -0.282576 | -0.574150 | -0.530945 | -0.488370 | 1.060932 |
276 rows × 57 columns
from sklearn.decomposition import PCA
# Separate features and target variables
features = df.drop([ "p00_1200", "p10_1200", "p00u_1200", "p10u_1200", "p00r_1200", "p10r_1200", "p00_30", "p10_30", "p00u_30", "p10u_30", "p00r_30", "p10r_30", "p00_75", "p10_75", "p00u_75", "p10u_75", "p00r_75", "p10r_75", "p00_150", "p10_150", "p00u_150", "p10u_150", "p00r_150", "p10r_150", "p00_600", "p10_600", "p00u_600", "p10u_600", "p00r_600", "p10r_600", "p00_300", "p10_300", "p00u_300", "p10u_300", "p00r_300", "p10r_300"], axis=1)
target_variables = df[[ "p00_1200", "p10_1200", "p00u_1200", "p10u_1200", "p00r_1200", "p10r_1200", "p00_30", "p10_30", "p00u_30", "p10u_30", "p00r_30", "p10r_30", "p00_75", "p10_75", "p00u_75", "p10u_75", "p00r_75", "p10r_75", "p00_150", "p10_150", "p00u_150", "p10u_150", "p00r_150", "p10r_150", "p00_600", "p10_600", "p00u_600", "p10u_600", "p00r_600", "p10r_600", "p00_300", "p10_300", "p00u_300", "p10u_300", "p00r_300", "p10r_300"]]
# Apply dimensionality reduction using PCA
pca = PCA(n_components=2) # Set the desired number of components
features_reduced = pca.fit_transform(features)
# Create a new DataFrame for the reduced features
df_reduced = pd.DataFrame(features_reduced, columns=['PC1', 'PC2'])
# Concatenate the reduced features with the target variables
df_combined = pd.concat([df_reduced, target_variables], axis=1)
df_reduced
| PC1 | PC2 | |
|---|---|---|
| 0 | -2.329699 | 1.201499 |
| 1 | -2.724107 | -0.899067 |
| 2 | -0.970523 | -0.068136 |
| 3 | -3.801980 | -0.339716 |
| 4 | -1.927433 | -0.712879 |
| ... | ... | ... |
| 271 | 3.797920 | -2.980111 |
| 272 | -1.871871 | 0.237314 |
| 273 | 2.285090 | -1.486060 |
| 274 | -1.308275 | -0.415028 |
| 275 | -1.430205 | 2.411526 |
276 rows × 2 columns
target_variables
| p00_1200 | p10_1200 | p00u_1200 | p10u_1200 | p00r_1200 | p10r_1200 | p00_30 | p10_30 | p00u_30 | p10u_30 | ... | p00u_600 | p10u_600 | p00r_600 | p10r_600 | p00_300 | p10_300 | p00u_300 | p10u_300 | p00r_300 | p10r_300 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | -0.508016 | -0.554848 | -0.660152 | -0.734917 | -0.282518 | -0.308726 | 1.307545 | 1.234529 | 1.464840 | 1.379198 | ... | -1.198856 | -1.233763 | -0.622001 | -0.599107 | -1.136296 | -1.125151 | -1.198046 | -1.215751 | -0.675829 | -0.636833 |
| 1 | -0.731805 | -0.679515 | -0.953322 | -0.919337 | -0.404765 | -0.361318 | -0.607961 | -0.582347 | -0.534148 | -0.512303 | ... | -0.931959 | -0.907064 | -0.360560 | -0.317110 | -0.600261 | -0.556108 | -0.736024 | -0.708998 | -0.193095 | -0.156917 |
| 2 | -0.916580 | -0.857975 | -1.120005 | -1.079853 | -0.576372 | -0.526636 | -0.483534 | -0.456906 | -0.410897 | -0.388234 | ... | -0.326982 | -0.245381 | -0.386586 | -0.339928 | 0.496365 | 0.605076 | 0.779507 | 0.935261 | -0.111894 | -0.068467 |
| 3 | -0.813688 | -0.764634 | -0.841270 | -0.801030 | -0.655143 | -0.609732 | -0.558129 | -0.534108 | -0.468648 | -0.447666 | ... | -1.038341 | -1.026704 | -0.628250 | -0.584963 | -1.094991 | -1.071174 | -1.162423 | -1.166418 | -0.638664 | -0.593155 |
| 4 | 0.029799 | 0.051246 | 0.148003 | 0.179467 | -0.085873 | -0.068557 | -0.600080 | -0.574276 | -0.543570 | -0.521872 | ... | -0.713870 | -0.672779 | -0.408781 | -0.367127 | -0.728155 | -0.685837 | -0.714859 | -0.682794 | -0.517095 | -0.473250 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | 1.899641 | 1.913771 | 1.051898 | 1.110167 | 2.384831 | 2.304732 | -0.392303 | -0.377247 | -0.430769 | -0.413749 | ... | 0.717522 | 0.768739 | 1.553292 | 1.483419 | 2.251499 | 2.276462 | 1.746700 | 1.828051 | 2.335818 | 2.210780 |
| 272 | -0.820254 | -0.771264 | -0.786267 | -0.743154 | -0.718363 | -0.671430 | -0.549863 | -0.526056 | -0.473721 | -0.452860 | ... | -0.051293 | 0.024048 | -0.615747 | -0.572764 | 0.188036 | 0.253678 | 0.569365 | 0.671899 | -0.477951 | -0.437206 |
| 273 | 2.340021 | 2.270520 | 2.634711 | 2.644594 | 1.682191 | 1.579212 | -0.446240 | -0.434000 | -0.480364 | -0.462969 | ... | 0.077725 | 0.059601 | 0.144024 | 0.120417 | 0.570582 | 0.541617 | 0.941671 | 0.931923 | -0.201114 | -0.199622 |
| 274 | -0.037393 | -0.131383 | -0.234249 | -0.340844 | 0.153308 | 0.072083 | -0.195625 | -0.247802 | -0.062048 | -0.120870 | ... | -0.755498 | -0.870089 | -0.144182 | -0.223553 | -0.551699 | -0.640980 | -0.643647 | -0.744355 | -0.229645 | -0.287221 |
| 275 | -0.577300 | -0.524737 | -0.452401 | -0.391292 | -0.600271 | -0.556288 | 0.277647 | 0.303837 | 0.480277 | 0.499443 | ... | -0.488171 | -0.440802 | -0.578217 | -0.535978 | -0.464913 | -0.420298 | -0.330085 | -0.282576 | -0.530945 | -0.488370 |
276 rows × 36 columns
df_combined
| PC1 | PC2 | p00_1200 | p10_1200 | p00u_1200 | p10u_1200 | p00r_1200 | p10r_1200 | p00_30 | p10_30 | ... | p00u_600 | p10u_600 | p00r_600 | p10r_600 | p00_300 | p10_300 | p00u_300 | p10u_300 | p00r_300 | p10r_300 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | -2.329699 | 1.201499 | -0.508016 | -0.554848 | -0.660152 | -0.734917 | -0.282518 | -0.308726 | 1.307545 | 1.234529 | ... | -1.198856 | -1.233763 | -0.622001 | -0.599107 | -1.136296 | -1.125151 | -1.198046 | -1.215751 | -0.675829 | -0.636833 |
| 1 | -2.724107 | -0.899067 | -0.731805 | -0.679515 | -0.953322 | -0.919337 | -0.404765 | -0.361318 | -0.607961 | -0.582347 | ... | -0.931959 | -0.907064 | -0.360560 | -0.317110 | -0.600261 | -0.556108 | -0.736024 | -0.708998 | -0.193095 | -0.156917 |
| 2 | -0.970523 | -0.068136 | -0.916580 | -0.857975 | -1.120005 | -1.079853 | -0.576372 | -0.526636 | -0.483534 | -0.456906 | ... | -0.326982 | -0.245381 | -0.386586 | -0.339928 | 0.496365 | 0.605076 | 0.779507 | 0.935261 | -0.111894 | -0.068467 |
| 3 | -3.801980 | -0.339716 | -0.813688 | -0.764634 | -0.841270 | -0.801030 | -0.655143 | -0.609732 | -0.558129 | -0.534108 | ... | -1.038341 | -1.026704 | -0.628250 | -0.584963 | -1.094991 | -1.071174 | -1.162423 | -1.166418 | -0.638664 | -0.593155 |
| 4 | -1.927433 | -0.712879 | 0.029799 | 0.051246 | 0.148003 | 0.179467 | -0.085873 | -0.068557 | -0.600080 | -0.574276 | ... | -0.713870 | -0.672779 | -0.408781 | -0.367127 | -0.728155 | -0.685837 | -0.714859 | -0.682794 | -0.517095 | -0.473250 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 271 | 3.797920 | -2.980111 | 1.899641 | 1.913771 | 1.051898 | 1.110167 | 2.384831 | 2.304732 | -0.392303 | -0.377247 | ... | 0.717522 | 0.768739 | 1.553292 | 1.483419 | 2.251499 | 2.276462 | 1.746700 | 1.828051 | 2.335818 | 2.210780 |
| 272 | -1.871871 | 0.237314 | -0.820254 | -0.771264 | -0.786267 | -0.743154 | -0.718363 | -0.671430 | -0.549863 | -0.526056 | ... | -0.051293 | 0.024048 | -0.615747 | -0.572764 | 0.188036 | 0.253678 | 0.569365 | 0.671899 | -0.477951 | -0.437206 |
| 273 | 2.285090 | -1.486060 | 2.340021 | 2.270520 | 2.634711 | 2.644594 | 1.682191 | 1.579212 | -0.446240 | -0.434000 | ... | 0.077725 | 0.059601 | 0.144024 | 0.120417 | 0.570582 | 0.541617 | 0.941671 | 0.931923 | -0.201114 | -0.199622 |
| 274 | -1.308275 | -0.415028 | -0.037393 | -0.131383 | -0.234249 | -0.340844 | 0.153308 | 0.072083 | -0.195625 | -0.247802 | ... | -0.755498 | -0.870089 | -0.144182 | -0.223553 | -0.551699 | -0.640980 | -0.643647 | -0.744355 | -0.229645 | -0.287221 |
| 275 | -1.430205 | 2.411526 | -0.577300 | -0.524737 | -0.452401 | -0.391292 | -0.600271 | -0.556288 | 0.277647 | 0.303837 | ... | -0.488171 | -0.440802 | -0.578217 | -0.535978 | -0.464913 | -0.420298 | -0.330085 | -0.282576 | -0.530945 | -0.488370 |
276 rows × 38 columns
# Define the number of folds for cross-validation
n_splits = 5
kf = KFold(n_splits=n_splits, shuffle=True)
# Assuming you have multiple target variables named 'target_variable1', 'target_variable2', etc.
target_variables = [
"p00_1200", "p10_1200", "p00u_1200", "p10u_1200", "p00r_1200", "p10r_1200",
"p00_30", "p10_30", "p00u_30", "p10u_30", "p00r_30", "p10r_30",
"p00_75", "p10_75", "p00u_75", "p10u_75", "p00r_75", "p10r_75",
"p00_150", "p10_150", "p00u_150", "p10u_150", "p00r_150", "p10r_150",
"p00_600", "p10_600", "p00u_600", "p10u_600", "p00r_600", "p10r_600",
"p00_300", "p10_300", "p00u_300", "p10u_300", "p00r_300", "p10r_300"
]
from sklearn.model_selection import KFold, train_test_split
from sklearn.metrics import mean_absolute_error, mean_squared_error
import numpy as np
# Define the number of folds for cross-validation
n_splits = 5
kf = KFold(n_splits=n_splits, shuffle=True)
# Define lists to store the errors for each target variable
rmse_list = []
mae_list = []
# Split the data into train and test sets
X_train, X_test, y_train, y_test = train_test_split(df_combined.drop(target_variables, axis=1),
df_combined[target_variables],
test_size=0.2,
random_state=42)
# Iterate over the folds
for train_index, val_index in kf.split(X_train):
# Get the training and validation sets
X_train_fold, X_val = X_train.iloc[train_index], X_train.iloc[val_index]
y_train_fold, y_val = y_train.iloc[train_index], y_train.iloc[val_index]
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_squared_error, mean_absolute_error
import numpy as np
# Initialize the Random Forest regressor
model1 = RandomForestRegressor(n_estimators=100, random_state=42)
# Fit the model on the training fold
model1.fit(X_train_fold, y_train_fold)
# Predict on the validation set
y_pred_val1 = model1.predict(X_val)
# Define lists to store the errors for each target variable
rmse_list2 = []
mae_list2 = []
# Calculate the evaluation metrics (RMSE and MAE) for each target variable
for i, target_variable in enumerate(target_variables):
rmse_val1 = np.sqrt(mean_squared_error(y_val[target_variable], y_pred_val1[:, i]))
mae_val1 = mean_absolute_error(y_val[target_variable], y_pred_val1[:, i])
# Append the errors to the respective lists
rmse_list2.append(rmse_val1)
mae_list2.append(mae_val1)
print("RMSE for", target_variable, ":", rmse_val1)
print("MAE for", target_variable, ":", mae_val1)
RMSE for p00_1200 : 0.28053487099249796 MAE for p00_1200 : 0.1948436912548931 RMSE for p10_1200 : 0.3206282093604051 MAE for p10_1200 : 0.20642821311331963 RMSE for p00u_1200 : 0.3565035541850463 MAE for p00u_1200 : 0.26555113821735593 RMSE for p10u_1200 : 0.3622224277524904 MAE for p10u_1200 : 0.27207519064585567 RMSE for p00r_1200 : 0.47642499041156905 MAE for p00r_1200 : 0.18388689357518662 RMSE for p10r_1200 : 0.5218983496828521 MAE for p10r_1200 : 0.18426611788619127 RMSE for p00_30 : 0.33799139722089244 MAE for p00_30 : 0.200106464483822 RMSE for p10_30 : 0.3393117880326379 MAE for p10_30 : 0.19360788731632186 RMSE for p00u_30 : 0.37403049986873416 MAE for p00u_30 : 0.22111349088298954 RMSE for p10u_30 : 0.36165187894661205 MAE for p10u_30 : 0.20986730541809792 RMSE for p00r_30 : 1.089285288788809 MAE for p00r_30 : 0.3349170967042949 RMSE for p10r_30 : 1.155367559660732 MAE for p10r_30 : 0.33726318152906315 RMSE for p00_75 : 0.4116671794902733 MAE for p00_75 : 0.22409868930526253 RMSE for p10_75 : 0.4346887488196657 MAE for p10_75 : 0.22667021890827496 RMSE for p00u_75 : 0.39569698453578894 MAE for p00u_75 : 0.21799179733602395 RMSE for p10u_75 : 0.3942956845865981 MAE for p10u_75 : 0.21414695485501037 RMSE for p00r_75 : 1.2143681756879294 MAE for p00r_75 : 0.33294696940790414 RMSE for p10r_75 : 1.28368633089651 MAE for p10r_75 : 0.33357030579982994 RMSE for p00_150 : 0.7169390747541178 MAE for p00_150 : 0.3459846141737994 RMSE for p10_150 : 0.7855824402944899 MAE for p10_150 : 0.35603813052017 RMSE for p00u_150 : 0.5129264113113432 MAE for p00u_150 : 0.35741779300718685 RMSE for p10u_150 : 0.5422900688976562 MAE for p10u_150 : 0.36746998695269467 RMSE for p00r_150 : 1.205820247489527 MAE for p00r_150 : 0.29594483970705054 RMSE for p10r_150 : 1.2662874090582625 MAE for p10r_150 : 0.29457922878080894 RMSE for p00_600 : 0.24538479594815193 MAE for p00_600 : 0.14214559061796664 RMSE for p10_600 : 0.29085383984553653 MAE for p10_600 : 0.1494993988723669 RMSE for p00u_600 : 0.32346407368869823 MAE for p00u_600 : 0.23903389700483865 RMSE for p10u_600 : 0.324437060087517 MAE for p10u_600 : 0.2424339395463642 RMSE for p00r_600 : 0.5837132406335707 MAE for p00r_600 : 0.19380854468077482 RMSE for p10r_600 : 0.6311034000067061 MAE for p10r_600 : 0.1911446771486567 RMSE for p00_300 : 0.4718167875575159 MAE for p00_300 : 0.2674840344721814 RMSE for p10_300 : 0.5207533074305426 MAE for p10_300 : 0.2815552539663015 RMSE for p00u_300 : 0.4506709386820878 MAE for p00u_300 : 0.30844367851577875 RMSE for p10u_300 : 0.4730017497075956 MAE for p10u_300 : 0.3238295224995055 RMSE for p00r_300 : 0.818520411878747 MAE for p00r_300 : 0.22149873802055808 RMSE for p10r_300 : 0.8568042640036099 MAE for p10r_300 : 0.21955155259077025
# Initialize the Random Forest regressor
model1 = RandomForestRegressor(n_estimators=100, random_state=42)
# Fit the model on the entire training set
model1.fit(X_train, y_train)
# Predict on the test set
y_pred_test1 = model1.predict(X_test)
# Define lists to store the errors for each target variable
rmse_list3 = []
mae_list3 = []
# Calculate the evaluation metrics (RMSE and MAE) for each target variable on the test set
for i, target_variable in enumerate(target_variables):
rmse_test1 = np.sqrt(mean_squared_error(y_test[target_variable], y_pred_test1[:, i]))
mae_test1 = mean_absolute_error(y_test[target_variable], y_pred_test1[:, i])
# Append the errors to the respective lists
rmse_list3.append(rmse_test1)
mae_list3.append(mae_test1)
print("Test Set - RMSE for", target_variable, ":", rmse_test1)
print("Test Set - MAE for", target_variable, ":", mae_test1)
Test Set - RMSE for p00_1200 : 0.45280389201585375 Test Set - MAE for p00_1200 : 0.2923768780241364 Test Set - RMSE for p10_1200 : 0.4656432253501561 Test Set - MAE for p10_1200 : 0.2922645250991608 Test Set - RMSE for p00u_1200 : 0.508848962579067 Test Set - MAE for p00u_1200 : 0.33957099187181466 Test Set - RMSE for p10u_1200 : 0.5284038193915708 Test Set - MAE for p10u_1200 : 0.355275704426346 Test Set - RMSE for p00r_1200 : 0.46037116621014496 Test Set - MAE for p00r_1200 : 0.2543251069726749 Test Set - RMSE for p10r_1200 : 0.4704835818949202 Test Set - MAE for p10r_1200 : 0.23690445526606377 Test Set - RMSE for p00_30 : 0.5773095102798528 Test Set - MAE for p00_30 : 0.2900682542197274 Test Set - RMSE for p10_30 : 0.5005143704087691 Test Set - MAE for p10_30 : 0.26423216443018277 Test Set - RMSE for p00u_30 : 0.6358139995390857 Test Set - MAE for p00u_30 : 0.2999998645748043 Test Set - RMSE for p10u_30 : 0.5459368296141377 Test Set - MAE for p10u_30 : 0.2705874461158171 Test Set - RMSE for p00r_30 : 0.5442335652480189 Test Set - MAE for p00r_30 : 0.3090926860882162 Test Set - RMSE for p10r_30 : 0.5474480246604531 Test Set - MAE for p10r_30 : 0.3066609688663523 Test Set - RMSE for p00_75 : 0.3533560511009237 Test Set - MAE for p00_75 : 0.2251331898052143 Test Set - RMSE for p10_75 : 0.3674915025837975 Test Set - MAE for p10_75 : 0.23006098314645068 Test Set - RMSE for p00u_75 : 0.374789062484832 Test Set - MAE for p00u_75 : 0.237680399324769 Test Set - RMSE for p10u_75 : 0.3794550173699248 Test Set - MAE for p10u_75 : 0.24138659244056507 Test Set - RMSE for p00r_75 : 0.5171583569175715 Test Set - MAE for p00r_75 : 0.2777236306994814 Test Set - RMSE for p10r_75 : 0.5276236667763128 Test Set - MAE for p10r_75 : 0.2753680055067304 Test Set - RMSE for p00_150 : 0.5634481767377898 Test Set - MAE for p00_150 : 0.3253371966932 Test Set - RMSE for p10_150 : 0.5877941042173158 Test Set - MAE for p10_150 : 0.33601448650851473 Test Set - RMSE for p00u_150 : 0.6317719209108424 Test Set - MAE for p00u_150 : 0.36724731023095875 Test Set - RMSE for p10u_150 : 0.6644140016736902 Test Set - MAE for p10u_150 : 0.3800719390982543 Test Set - RMSE for p00r_150 : 0.4197891778446871 Test Set - MAE for p00r_150 : 0.21572103927614003 Test Set - RMSE for p10r_150 : 0.4345369266202263 Test Set - MAE for p10r_150 : 0.21015104496946038 Test Set - RMSE for p00_600 : 0.2811236668624168 Test Set - MAE for p00_600 : 0.19529984481674828 Test Set - RMSE for p10_600 : 0.3087316531943777 Test Set - MAE for p10_600 : 0.21323143424064714 Test Set - RMSE for p00u_600 : 0.3563992151905941 Test Set - MAE for p00u_600 : 0.24838230840520037 Test Set - RMSE for p10u_600 : 0.38356833868655626 Test Set - MAE for p10u_600 : 0.26537127392980053 Test Set - RMSE for p00r_600 : 0.3379746211463177 Test Set - MAE for p00r_600 : 0.18612656159199456 Test Set - RMSE for p10r_600 : 0.3558154743548304 Test Set - MAE for p10r_600 : 0.18769353723603938 Test Set - RMSE for p00_300 : 0.42559849194244254 Test Set - MAE for p00_300 : 0.3107006820754439 Test Set - RMSE for p10_300 : 0.4461664951580049 Test Set - MAE for p10_300 : 0.32539219101383404 Test Set - RMSE for p00u_300 : 0.5513268289705853 Test Set - MAE for p00u_300 : 0.4119960761572056 Test Set - RMSE for p10u_300 : 0.5813459405496905 Test Set - MAE for p10u_300 : 0.4340357334863906 Test Set - RMSE for p00r_300 : 0.2763603526889699 Test Set - MAE for p00r_300 : 0.17326067914672577 Test Set - RMSE for p10r_300 : 0.282141141087941 Test Set - MAE for p10r_300 : 0.17144293171428357
# Calculate the mean error for each metric
mean_rmse2 = np.mean(rmse_list2)
mean_mae2 = np.mean(mae_list2)
print("Mean RMSE TRAIN:", mean_rmse2)
print("Mean MAE TRAIN:", mean_mae2)
mean_rmse3 = np.mean(rmse_list3)
mean_mae3 = np.mean(mae_list3)
print("Mean RMSE TEST:", mean_rmse3)
print("Mean MAE TEST:", mean_mae3)
Mean RMSE TRAIN: 0.5869617622276588 Mean MAE TRAIN: 0.25420041743659644 Mean RMSE TEST: 0.4623886425628519 Mean MAE TEST: 0.2765607810408153
from sklearn.metrics import r2_score
# Calculate the R-squared for the test set
r2_test = r2_score(y_test, y_pred_test1)
# Calculate the adjusted R-squared for the test set
n_test = X_test.shape[0] # Number of samples in the test set
p_test = X_test.shape[1] # Number of features in the test set
adj_r2_test = 1 - (1 - r2_test) * ((n_test - 1) / (n_test - p_test - 1))
# Print the adjusted R-squared for each target variable in the test set
print("Adjusted R^2 (Test):")
for i, target_variable in enumerate(target_variables):
print(target_variable, ":", adj_r2_test)
# Calculate the mean of the training set
mean_train = np.mean(y_train, axis=0)
# Calculate the mean of the test set
mean_test = np.mean(y_test, axis=0)
# Print the mean of the training set for each target variable
print("Mean (Train):")
for i, target_variable in enumerate(target_variables):
print(target_variable, ":", mean_train[i])
# Print the mean of the test set for each target variable
print("Mean (Test):")
for i, target_variable in enumerate(target_variables):
print(target_variable, ":", mean_test[i])
Adjusted R^2 (Test): p00_1200 : 0.7480867771763906 p10_1200 : 0.7480867771763906 p00u_1200 : 0.7480867771763906 p10u_1200 : 0.7480867771763906 p00r_1200 : 0.7480867771763906 p10r_1200 : 0.7480867771763906 p00_30 : 0.7480867771763906 p10_30 : 0.7480867771763906 p00u_30 : 0.7480867771763906 p10u_30 : 0.7480867771763906 p00r_30 : 0.7480867771763906 p10r_30 : 0.7480867771763906 p00_75 : 0.7480867771763906 p10_75 : 0.7480867771763906 p00u_75 : 0.7480867771763906 p10u_75 : 0.7480867771763906 p00r_75 : 0.7480867771763906 p10r_75 : 0.7480867771763906 p00_150 : 0.7480867771763906 p10_150 : 0.7480867771763906 p00u_150 : 0.7480867771763906 p10u_150 : 0.7480867771763906 p00r_150 : 0.7480867771763906 p10r_150 : 0.7480867771763906 p00_600 : 0.7480867771763906 p10_600 : 0.7480867771763906 p00u_600 : 0.7480867771763906 p10u_600 : 0.7480867771763906 p00r_600 : 0.7480867771763906 p10r_600 : 0.7480867771763906 p00_300 : 0.7480867771763906 p10_300 : 0.7480867771763906 p00u_300 : 0.7480867771763906 p10u_300 : 0.7480867771763906 p00r_300 : 0.7480867771763906 p10r_300 : 0.7480867771763906 Mean (Train): p00_1200 : -0.04516698280082065 p10_1200 : -0.04530860553563185 p00u_1200 : -0.03606130414862029 p10u_1200 : -0.03657654740196988 p00r_1200 : -0.04634645070212615 p10r_1200 : -0.04561417782626307 p00_30 : -0.019903332213403867 p10_30 : -0.015143898945274558 p00u_30 : -0.022858175861743327 p10u_30 : -0.01796218216905223 p00r_30 : 0.004775071550874152 p10r_30 : 0.00622943354298093 p00_75 : -0.0038051759838948446 p10_75 : -0.0015021363601061411 p00u_75 : -0.002774865462601772 p10u_75 : -0.0004571324316705533 p00r_75 : -0.0050741720841499345 p10r_75 : -0.0038687765180764927 p00_150 : 0.008511861411043408 p10_150 : 0.009158548709518315 p00u_150 : 0.013756918171685933 p10u_150 : 0.014348939766580703 p00r_150 : -0.006737598983122436 p10r_150 : -0.005438501559455057 p00_600 : -0.017186524991065294 p10_600 : -0.01761569853034427 p00u_600 : -0.010346543012594326 p10u_600 : -0.010567661218205467 p00r_600 : -0.02147201395543675 p10r_600 : -0.021356990478684168 p00_300 : -0.011591097601375834 p10_300 : -0.010689836397070525 p00u_300 : -0.005706823105841629 p10u_300 : -0.004751638462402846 p00r_300 : -0.01724637497710254 p10r_300 : -0.015976742617020593 Mean (Test): p00_1200 : 0.17744171814608106 p10_1200 : 0.17799809317569668 p00u_1200 : 0.14166940915529447 p10u_1200 : 0.14369357907916783 p00r_1200 : 0.182075342044067 p10r_1200 : 0.17919855574603374 p00_30 : 0.07819166226694443 p10_30 : 0.05949388871357815 p00u_30 : 0.08979997659970547 p10u_30 : 0.07056571566413351 p00r_30 : -0.018759209664148912 p10r_30 : -0.02447277463313952 p00_75 : 0.014948905651015698 p10_75 : 0.005901249986131444 p00u_75 : 0.010901257174506724 p10u_75 : 0.0017958774101349353 p00r_75 : 0.019934247473446094 p10r_75 : 0.01519876489244319 p00_150 : -0.03343945554338528 p10_150 : -0.03598001278739349 p00u_150 : -0.054045035674480255 p10u_150 : -0.056370834797282096 p00r_150 : 0.026469138862266716 p10r_150 : 0.021365541840715707 p00_600 : 0.06751849103632857 p10_600 : 0.06920452994063839 p00u_600 : 0.04064713326376405 p10u_600 : 0.041515811928664985 p00r_600 : 0.08435434053921606 p10r_600 : 0.08390246259483028 p00_300 : 0.04553645486254781 p10_300 : 0.04199578584563344 p00u_300 : 0.022419662201520713 p10u_300 : 0.01866715110229638 p00r_300 : 0.06775361598147389 p10r_300 : 0.06276577456686654